Prosiding SISFOTEK

Pelaksanaan Supervisi Akademik Berbasis Coaching Terhadap Kinerja Guru di UPT SPF SD Negeri 3 Kasimpureng

Muhammad Arfin — 2024-10-15

This study aims to determine teacher performance through the implementation of coaching-based academic supervision by school principals. The subjects in this study were principals and teachers of UPT SPF SD Negeri 3 Kasimpureng. This research used descriptive method with qualitative approach. Data collection techniques were interview, observation and documentation study. Data were analysed using reduction, presentation and conclusion techniques. The results showed: (1) The coaching-based academic supervision programme is made based on one of the school's strategic plans, namely improving teacher performance in managing effective learning; (2) The implementation of coaching-based academic supervision uses practical, objective, humanist, sustainable and constructive principles through approaches and techniques based on teacher characteristics; (3) School principals provide guidance and coaching, then teachers are recommended to attend training, technical assistance, and competency improvement workshops; (4) Supporting factors for coaching-based academic supervision are teachers‘ willingness to learn, teachers’ good perception of coaching-based academic supervision, principals' knowledge, and harmonious relationships among school members. The obstacles in coaching-based academic supervision are the principal's sudden external activities that disrupt the supervision schedule. There are no senior teachers who can assist the principal. Teachers were unable to attend the scheduled class visits.

Pentingnya Keamanan Data Dalam Era Digital: Refleksi Terhadap Serangan Hacker Pada Pusat Data Nasional Indonesia

Rafli Al Ihsan — 2024-10-15

In the digital era, data security has become a crucial issue for many countries, including Indonesia, especially after the hacker attack on Indonesia's National Data Center exposed the vulnerability of the system and its impact on national security and public trust. This journal aims to investigate the importance of data security in the digital era with a focus on the hacker attack that occurred on the PDN. This research uses the literature study method to explore the importance of data security, analyze the level of vulnerability of the National Data Center to cyberattacks, its impact on government stability and operations, and formulate strategies and policies that can be implemented to strengthen data defense. The results show that in addition to improved security technology, strict policies and good human resource education, inter-agency cooperation and international collaboration are also very important in building a resilient security system.

Analisis Dan Perancangan Keamanan Frontend Dalam Aplikasi Web: XSS dan CSRF

Vincent Laurensius Hambaya — 2024-10-15

Definitely Secure Bank (DSB) is a web application designed to model digital bank financial transactions. In the early stages of development, this DSB application has several security vulnerabilities, including Cross-Site Scripting (XSS) attacks with a non-persistent type on the web help page and Cross-Site Request Forgery (CSRF) attacks on the financial transaction process. In the DSB application and other modern web applications, the most common vulnerabilities encountered are vulnerabilities to XSS and CSRF attacks. XSS attacks occur when someone successfully injects malicious javascript scripts into a web page, which can be executed from the user's browser. While CSRF attacks are attacks to trick users into sending unwanted requests to trusted websites. This study aims to analyze frontend security vulnerabilities on DSB and implement solutions to prevent them. The analysis is carried out by identifying vulnerable points in the application and evaluating their potential for exploitation. The proposed solution to prevent XSS attacks is to apply input sanitation to all user-entered data on the help page. Input sanitation will clean data from malicious scripts before being processed by the system. To prevent CSRF attacks, the proposed solution is to use CSRF tokens when making transactions on DSB. A CSRF token is an encrypted random value that is added to each HTTP request and verified by the server. Implementing these solutions can improve DSB security and prevent exploitation of XSS and CSRF attack vulnerabilities.

Pemanfaatan Analisis Bibliometrik Menggunakan VOSViewer untuk Pemetaan Tren Publikasi TPACK dan Critical Thinking Skills

Andi Alim Syahri — 2024-10-15

This study aims to analyze the development of studies related to "TPACK" and "Critical Thinking Skills" based on bibliometric analysis of a number of journal articles published in the Google Scholar database. This research identifies scientific gaps as a reference for further research. TPACK and Critical Thinking Skills have an important role in realizing 21st century learning in education. This research method uses a bibliometric analysis approach by collecting article data from 2019 to 2023. Data collection was supported by VOSviewer software using the keywords "TPACK" and "Critical Thinking Skills", and a total of 500 articles were analyzed. The results showed an increasing trend of research on TPACK and Critical Thinking Skills, and several topics/keywords were found that can be used as a basis for further research. The bibliometric analysis provides valuable information and knowledge about the development of "TPACK" and "Critical Thinking Skills" research, and the results of this study can serve as a basis for possible new research in the future. The findings can provide important information for educational researchers and practitioners in understanding current research trends and also help set the direction for more in-depth research in the future.

Pemanfaatan Teknologi Digital Untuk Meningkatkan Kemampuan Literasi dan Numerasi Anak Usia Dini

Sri Sufliati Romba — 2024-10-21

This study aims to determine the effectiveness of using digital technology media to improve early childhood numeracy literacy skills in the learning process. If children have good literacy and numeracy skills at an early age, they are building the foundation of knowledge and skills that they need to learn at a higher level. Therefore, effective and innovative learning approaches are needed, such as the use of digital technology media which is utilised to improve children's literacy skills in a fun and interactive way from an early age. This type of research uses a descriptive quantitative approach, with a population of 30 children. Data collection techniques were carried out using observation and documentation methods and using data processing normality test, homogeneity test, and one-sample test. In the One sample test, the Significance Two-Sided p value is 0.01, <0.05 and the Mean difference of the initial observation is 48.500 and the second observation is 70.167, it is found that there is a difference in the average increase from the initial observation and the second observation. Based on the results of the calculation, it is concluded that the use of Digital Technology media in learning greatly helps the development of Early Childhood Literacy and Numeracy, namely in terms of creativity, reading skills, counting skills, and writing skills, and encourages interest/reading habits at Bukit Permai Agang Je’ne Kindergarten.

Efektivitas Layanan Konseling dengan Teknik Kontrak Perilaku Untuk Menurunkan Perilaku Membolos

Hadrawi — 2024-10-21

This study aims to evaluate the effectiveness of counseling services using behavior contract techniques in reducing truancy behavior among students. The behavior contract technique was employed as an intervention to change students' negative behaviors, with the expectation of promoting positive behavior following the implementation of this intervention. The study utilized a pre-experimental design with a one-group pretest-posttest design. The research subjects were eighth-grade students with high levels of truancy behavior, totalling 8 students. Data were collected through questionnaires measuring truancy behavior before and after the intervention. The results showed a significant change in the experimental group after receiving the intervention using the behavior contract technique. The average posttest scores increased significantly compared to the pretest scores, indicating that this technique is effective in reducing truancy behavior. The analysis of independent t-test results also supported this conclusion, as there was a significant difference between the experimental group that received the intervention and the control group that did not receive the intervention. It can be concluded that the behavior contract technique is an effective method for reducing truancy behavior and can be applied as part of counseling services to improve student behavior in schools.

Penerapan Metode SDLC Waterfall Pada Sistem Pemesanan Makanan Menggunakan QR-Code Berbasis Website

Yolla Putri Ervanisari — 2024-10-22

Café Sudut Temu by Toastea, located in Cirahayu Tegalega Street, Central Bogor, was established in 2015. The manual booking system in place at Café Sudut Temu is currently inefficient and vulnerable to error, resulting in lengthy waiting times, order errors, and challenges in inventory management. Therefore, this research is planning to build a QR code-based food ordering system through a website. The ordering system in this study was developed using the Waterfall methodology and the application was designed using the Laravel PHP framework. The design phase begins with the collection of requirements, the creation of design, the implementation or development of the system and ends with testing. This research results in a system that simplifies the ordering process, reduces errors, and improves operational efficiency.In addition, the responsive design with a mobile-friendly interface allows customers to order directly without having to wait for the help of the server. The system is expected to increase customer satisfaction and contribute to coffee growth amid increasing competition in the industry. The results of this research are a website-based application for ordering food and beverages using a QR Code on Café Sudut Temu.

Rancang Bangun Aplikasi Validator Tagihan Pada Kantor Pelayanan Perbendaharaan Negara Kota Palopo

Muh Khaifun — 2024-10-22

The research aims to design and create a payment bill validator application at the Palopo City State Treasury Service Office. This application is designed to facilitate KPPN staff in the process of channeling budgets to work units, as well as helping the process of validating accounts submitted by work units whether the account is valid or not. Data was collected through interviews, observations, and literature studies. The results showed that the developed application has a high level of usability, with an average score of 84% based on the System Usability Scale (SUS) assessment. This score falls into the “Very Feasible” category and indicates that the application is suitable for use. The application was also tested with whitebox testing techniques to ensure the program flow, logical structure, and procedures run well. The results of testing by users involved 30 respondents who gave an average rating of 84%, which is included in the “Very Good” category. This shows that the developed payment bill validator application has met user needs and is ready to be implemented at KPPN Palopo City.

Rancang Bangun Website Budaya Rongkong Sebagai Media Promosi Pariwisata

Richo Pratama — 2024-10-22

This study aims to build a website to introduce culture and tourism in Rongkong, North Luwu Regency, so that Indonesian people can get to know the culture in Rongkong. The data collection techniques used by the author are by conducting observations, interviews and literature studies. The research method used is waterfall and uses black box testing techniques. From the results of the research conducted, it can be concluded that the Rongkong Cultural Website as a Tourism Promotion Media is feasible to use because the test results can be accepted by the system and are ready to use.

Analisis Kinerja Jaringan WLAN Menggunakan Metode TCBH pada SMAN 7 Luwu Utara

Umi Aulia — 2024-10-22

This research aims to describe the network performance at SMAN 7 North Luwu. The research method used is qualitative. The qualitative method is a research study that is descriptive in nature and tends to use analysis and is more visible in the data collection processes and techniques carried out, namely observation, interviews and literature studies. Based on the results of research on network performance at SMAN 7 North Luwu from the beginning to the research stage, it can be concluded that after analyzing the network performance by implementing Qos at the agency, it was said to be quite good, but at some times it was said to be moderate due to delays in the network at SMAN 7 Luwu. North, therefore we need a system to analyze a network that emphasizes how to monitor and measure performance to see the quality of service from how much network performance on infrastructure such as upload and download speed, by measuring bandwidth, delay, packet loss, throughput and jitter parameters. by using the Axence NetTools v5 application at SMAN 7 North Luwu

Sistem Informasi Pengarsipan Surat Masuk dan Surat Keluar Berbasis Website pada PT. Zhanjiang Arta Kuopasific Indonesia

Nurul Masita — 2024-10-22

The purpose of this study is to design a website-based information system for archiving incoming and outgoing mail at PT. Zhanjiang Arta Kuopasific Indonesia. The type of research used is R&D (Research and Development) while the application development method used is the Rapid Application Development (RAD) method which consists of the planning phase, workshop design phase, and implementation phase. Data collection is done by observation, interviews, and literature studies. This website is designed using sublime text software, phpMyAdmin as a database, and the bootstrap 4 framework as css and javascript. Based on the results of black box testing, it states that the website system for archiving incoming and outgoing mail at PT. Zhanjiang Arta Kuopasific Indonesia can run well and produce results that are in accordance with expectations. This website is designed using the UML (Unified Modeling Language) modeling method consisting of use case diagrams, Activity diagrams, sequence diagrams and class diagrams. Based on the results of the web design validation given to 2 validators, the final score was 4.0, which means that the web design assessment is in the good category. Then from the results of the interface design validation given to 2 validators, the final score was 4.0, which means that the interface design assessment is in the strongly agree category. Furthermore, from the results of the UML validation given to 2 validators, the final score was 4.0, which means that the UML assessment is in the agree category. Then from the results of the database validation given to 2 validators, the final score was 4.0, which means that the database assessment is in the strongly agree category.

Rancang Bangun Sistem Informasi pada Puskesmas Bara Permai Berbasis Website

Dony Tri Putra — 2024-10-22

This study aims to build an information system at the Bara Permai Health Center in Palopo City based on a website. This application is expected to help and facilitate the archiving of patient data at the Bara Permai Health Center in Palopo City. This research was conducted at the Bara Permai Health Center in Palopo City. The type of research used in this study is Research and Development (R&D) using the waterfall research development method. The data collection methods used are observation, interviews and literature studies. The design of the system model uses the Unified Modeling Language (UML) approach consisting of Use Case Diagrams, Activity Diagrams, Sequence Diagrams, and Class Diagrams. The results of this study are in the form of an application for archiving patient data, drug data, employee data, and doctor data built using the Visual Studio Code programming language, as application creation software, XAMPP as a MySQL database web server for report generation. The testing used in this system is the white box testing technique, where all displays and features in this system have functioned well so that this application can be used at the Bara Permai Health Center in Palopo City

Analisis Sentimen Pandangan Masyarakat Terhadap Uji Emisi di Twitter Menggunakan Metode Support Vector Machine

Aziz Musthafa — 2024-10-22

Air pollution caused by motor vehicles is a major problem today. To reduce the dangers of air pollution and pollution caused by increasing motor vehicle users, the government immediately enacted legal action against vehicles that did not conduct or pass emission tests. From these government actions there are various kinds of public opinions, especially on social media twitter. This study aims to classify public sentiment towards emission tests expressed on twitter social media by collecting comment data and labeling it as positive, negative, and neutral. The method used in this research with data amounting to 3459 comments uses Support Vector Machine (SVM). Meanwhile, to measure the performance of the SVM method using Confusion Matrix. The results of testing using the SVM method resulted in an accuracy of 76%, and the results of the classification obtained more positive class values. This states that the policies made by the government related to emission testing have received a positive response from the public.

Analisis Sentimen Pandangan Masyarakat Terhadap Piala Dunia U-17 Menggunakan Teknik Teks Mining

Aziz Musthafa — 2024-10-22

One of the most loved sports by people around the world is football. Indonesia is one of the countries with the most football fans in the world. Indonesia is one of the countries with the largest number of football fans in the world, with 77% of the Indonesian population interested in football. Based on research analysis, Indonesia was selected to host the 2023 U-17 World Cup. The decision was made after the International Football Federation (FIFA) granted hosting rights. Specifically to the President of the Indonesian Football Federation (PSSI). This research aims to classify public opinion related to the event from twitter social media into 3 class categories, namely neutral, positive and negative. In this research, the methods used are Naïve Bayes algorithm and Support Vector Machine (SVM) algorithm. The classification results show that the naïve bayes method has an accuracy result of 0.73 while for the Support Vector Machine method the accuracy value obtained is 0.84 which shows that Support Vector Machine has better accuracy than Naive Bayes. Based on the model classification, positive sentiment has the highest percentage of other classes with a percentage of 35%, followed by negative sentiment with a percentage of 31% and neutral sentiment is the minority class with a percentage of 33%. From the percentage obtained, it can be concluded that the public has a positive view of the organisation of the U-17 world cup in Indonesia. It is hoped that in the future this research can be improved and implemented better with additional algorithm methods or with a larger amount of data.

Penerapan Pola Arsitektur Model-View-ViewModel pada Aplikasi Pembelajaran Shorof Berbasis Mobile

Havidz Muhammad Iqbal — 2024-10-22

This research aims to develop an Android-based Basic Shorof learning application using Model-View-ViewModel (MVVM) architecture pattern. The background of this research focuses on the difficulties faced by Non KMI students at Darussalam Gontor University in understanding Shorof material, which is a major challenge in Arabic language learning. Many students have difficulty in understanding the basic concepts of Shorof, which is an important component in the overall mastery of the Arabic language. This research method includes data collection through questionnaires distributed to students. The purpose of this data collection was to identify the difficulties faced by students in learning Shorof. Analysis of the questionnaires showed that many students have difficulties in understanding the basic concepts of Shorof. This finding became the basis for the development of a learning application that is easy for students to use. The developed application uses MVVM approach to separate the business logic from the user interface. This approach facilitates future development, testing, and maintenance of the application. The features of this application include learning modules, quizzes, and Arabic vocabulary designed to strengthen students' understanding of Shorof material. Application testing involved a number of students as respondents to measure the effectiveness and efficiency of the application in improving their understanding of Shorof material. The test results showed that students experienced an increase in understanding after using this application. In conclusion, the application of MVVM architecture pattern in the development of Basic Shorof learning application can improve students' understanding effectively. This research is expected to have a positive impact on the development of educational applications in the future. Thus, this application is useful not only for students of Darussalam Gontor University, but also for the development of Arabic learning methods more broadly in various educational institutions.

Implementasi MVVM Dan Framework Jetpack Compose Pada Aplikasi Hukum Berbasis Android

Aziz Musthafa — 2024-10-22

This research discusses the development of Android-based legal applications using Model-View-ViewModel (MVVM) architecture and Jetpack Compose framework. The purpose of this research is to improve the access and understanding of the Indonesian people to legal aid through an efficient and user-friendly mobile application. The research method used is Software Development Life Cycle (SDLC) with a waterfall model that includes the stages of needs analysis, design, implementation, testing, and maintenance. Data was collected through a questionnaire distributed to 107 respondents aged 17-40 years to measure their understanding of the law and access to legal aid. The results of the analysis showed that 67% of the respondents knew how to get legal aid, but did not know the details of how. The developed app has several key features, such as a list of laws and regulations, AI Q&A, and lawyer consultation. The implementation of Jetpack Compose on the login, register, home, chatbot, regulations, and regulation details pages shows efficiency and ease in developing an interactive and responsive user interface. Application testing is carried out through verification by media experts, application users, and black box tests. The test results show that the application functions properly and meets user needs. The conclusion of this research is that the use of MVVM architecture and Jetpack Compose can speed up the development process and facilitate the maintenance of Android-based legal applications. This application is expected to provide practical and effective solutions in obtaining legal assistance and increasing legal understanding among the people of Indonesia.

Implementasi Deep Learning dalam Pendeteksian Dini Penyakit Alzhaimer

Imam Mulyana — 2024-10-22

Alzheimer's Disease (AD), is a neurodegenerative condition that develops slowly and generally occurs in older people. The aim of this research is to optimize Deep Learning models so that they can process complex brain imaging data efficiently. The method used involves the use of a CNN (Convolutional Neural Network) network which is trained with a dataset of brain MRI images that have been processed and divided into subsets for training, validation and testing. The data used was taken from the Kaggle platform and processed using augmentation techniques with `ImageDataGenerator`. The research results show that the implemented model is able to achieve high accuracy in detecting structural and functional changes in the brain related to Alzheimer's. The loss and accuracy curves monitored during the training process show a positive trend, with accuracy reaching over 96% in just seven epochs. The main conclusion of this research is that Deep Learning technology has great potential in early detection of Alzheimer's disease, enabling earlier and more effective interventions to prevent or slow the progression of this disease, as well as improving the quality of life of individuals at risk.

Implementasi Business Intelligence dalam Meningkatkan Pembuatan Dashboard dailytracker pada PT.XYZ

Ricky Rivandy A’oetpah — 2024-10-22

Business intelligence (BI) is a technology infrastructure that analyzes data and generates reports to help managers make decisions. PT XYZ is a company engaged in insurance, which has many employees, especially in the IT and Operations divisions. Problems arise when a lot of employee daily work report data is not decomposed and cannot be analyzed by managers to make a decision. The purpose of this research is to optimize employee daily work report data with business intelligence methods in data visualization so that it can be easily analyzed and can be used as decision-making material for managers. The methods used in the research include analyzing user needs, designing business intelligence systems, implementing business intelligence systems, and testing as well as conducting qualitative methods in the form of interviews as user satisfaction surveys. The results of the application of business intelligence on the dailytracker dashboard at PT XYZ are feasible to use according to employees and managers. And the managers also gave a good response to the strategy implemented which is very informative in displaying data and can assist in analyzing data to make decisions within the company.

Sistem Penunjang Keputusan Penilaian Kinerja Menggunakan Metode Fuzzy Mamdani untuk Menentukan Status Karyawan

Lena Magdalena — 2024-10-22

Employee performance appraisal is a performance management process in the company that functions as one of the decision-making for employee performance appraisal. At the Cirebon Non-Container Terminal PTP, a performance assessment has been carried out, but there are weaknesses, one of which is an input error in conducting an assessment which can directly change several components of the performance assessment so that the performance assessment decision is not accurate. The creation of a performance appraisal decision support system to determine the status of employees using the fuzzy mamdani method, produces a decision on employee performance appraisal recommendations and serves as a basis for consideration to change the status of employees who are still on contract to permanent employees. In this study, the tool used is Matlab (Matrix Laboratory) to compare the results graphically and the decision support system to be designed. The fuzzy mamdani method is applied with three assessment criteria, namely good, sufficient, and poor, this helps in making monthly decisions regarding the results of performance appraisals which are then recapitulated at the end of the year. The results of the calculation between Matlab and the Decision Support System using the fuzzy mamdani method show that the final score has a difference that is not much different, meaning that the fuzzy mamdani method has proven to be effective for employee performance assessment by producing accurate assessment decisions.

Optimalisasi E-Commerce: Rekomendasi Terkomputerisasi Dan Keputusan Pelanggan Melalui Metode SUS

Julius Jerry Nolasco — 2024-10-23

The focus of this study is on the development of strategies to optimize E-Commerce performance by enhancing information systems. It highlights recommendation methods, automated calculations, and customer decision-making using the System Usability Scale (SUS) technique. The main objective is to improve the recommendation system, increase information management efficiency, and enhance user satisfaction within an E-Commerce setting. The methods employed include creating a recommendation system based on a product information management model utilizing the K-means algorithm, implementing technology suitability models in accounting information systems, and assessing with a hybrid SUS. Data collection will be crucial in supporting the research's goals. The findings will pinpoint areas for enhancing product recommendation relevance, showcasing user satisfaction, and displaying decision-making effectiveness on the E-Commerce platform. The conclusion stresses the significance of technological integration in shaping the E-Commerce business model and its potential to enrich the online shopping experience. The research proposes that novel marketing strategies in the digital economy era can heighten the competitiveness of E-Commerce companies. This investigation makes a substantial contribution to comprehending and crafting efficient E-Commerce information systems, with vital implications for enhancing business performance and delivering customer value in an ever-changing digital landscape.

Pengembangan Kompetensi Siswa dalam Pembelajaran dengan Menggunakan Metode Game-Based Learning

Nicholas Patrick Varian — 2024-10-23

Learning in classrooms is often seen as dull and lacking interaction, leading students to lose interest in understanding the material. To combat this, new teaching methods have been introduced, including interactive learning through games. Despite games' potential to boost motivation and engagement, further research is needed to understand Game-Based Learning's (GBL) specific impact on learning experiences, competency development, and student achievements. This study employs a quantitative approach, collecting data via surveys and tests on students using GBL. Hypotheses are tested through statistical analysis. Results reveal GBL's positive influence on students' learning experiences, with increased motivation, engagement, and comprehension of material. GBL also enhances students' competencies and improves learning outcomes. Thus, GBL emerges as an effective method for enhancing learning experiences, developing student competencies, and boosting academic achievements. Integrating GBL into educational curricula is crucial for improving learning quality and student outcomes.

Analisis Performa Dan Optimasi Bandwidth Jaringan Wifi Di Lingkungan Kampus

Angga Novita Prasetyo Ningrum — 2024-10-23

WiFi networks have become critical components in supporting academic and administrative activities in higher education institutions. Esa Unggul University, as a growing educational institution, faces challenges in ensuring the quality and reliability of its WiFi network as the number of users and bandwidth requirements increase. This study analyses the performance and optimises the bandwidth of the WiFi network in the Esa Unggul University environment. Through a qualitative approach with a case study, this research collects data through in-depth interviews, direct observations, and technical measurements. Analysis is conducted on access speed, connection stability, and bandwidth capacity in various campus areas. The research results identify several critical points affecting network performance and propose optimisation strategies that include infrastructure upgrades, configuration adjustments, and implementation of effective bandwidth management. The findings and recommendations from this study are expected to improve the quality of internet service at Esa Unggul University, better support academic and administrative activities, and provide valuable insights for other higher education institutions in managing their WiFi network infrastructure.

Penerapan Radio Frequency Identification (RFID) Untuk Efisiensi Inventaris Pada Toko Minimal

Irma Tiara — 2024-10-23

Minimal is a local Indonesian fashion brand which is famous for its minimalist and modern designs. Minimal's main store is located at Kota Kasablanka Mall, LG Floor, Jl. Casablanca Raya Kav. 88, South Jakarta. Problems arise from inefficient inventory management, such as stock inaccuracies, difficulties in product tracking, and the length of the inventory process. This has a negative impact on the store, including lost potential sales and decreased customer satisfaction. At a minimum, we also don't have an integrated system to manage inventory in real-time across all branches. The aim of this research is to implement an RFID (Radio Frequency Identification) system to increase inventory management efficiency and improve customer service. RFID is a technology that uses radio waves to identify and track objects automatically. Research methods include needs analysis, system design, RFID implementation, and performance evaluation. The results of implementing the RFID system at Minimal stores show a significant increase in inventory accuracy by 98%, a reduction in inventory time by 75%, and an increase in customer satisfaction by 30%.

Implementasi Optimasi NLP dan KNN untuk User Review Aplikasi SAMPEAN Cirebon

Mesi Febima — 2024-10-23

The use of information technology in the personnel administration process plays an active role in improving public services for civil servants (ASN) in the Cirebon City Government by providing accurate data for decision-making. One of the smart city applications that assists ASN in Cirebon City in supporting personnel administration activities is the SAMPEAN Cirebon City application. However, to ensure that this application is truly effective and meets user needs, it is important to analyze user reviews provided through application reviews. One effective method for analyzing user reviews is by using Natural Language Processing (NLP) and machine learning techniques. The NLP technique and classification model used is the KNN algorithm. The purpose of this research is to provide valuable input for application developers in improving the quality and performance of the SAMPEAN application. The research results show that by testing accuracy using the confusion matrix with K values of 3, 5, 7, and 9, it was found that K=9 provides the best performance with a balance between precision, recall, F1-Score, and accuracy. The model achieved a precision of 64%, recall of 90%, F1-Score of 75%, and accuracy of 62%. It can be concluded that with the optimization of the K parameter in KNN, the higher the K value, the higher the accuracy. This emphasizes the importance of selecting the right parameters to enhance the effectiveness of machine learning models in various Natural Language Processing (NLP) applications.

Studi Literatur: Optimalisasi Pembelajaran Pemrograman dengan Sistem Berbasis AI

Rizky Nur Azizah — 2024-10-23

Artificial intelligence (AI) has opened up new opportunities in various fields, including education. AI makes it possible to optimize the teaching-learning process in the context of programming learning, which is often considered challenging by many students. This research aims to explore the potential for optimizing programming learning through the implementation of an AI-based online learning system. The method used is a literature study, which involves researching various sources that discuss the use of AI in education, particularly in the context of programming learning. The literature approach includes analyzing and synthesizing data from journals, books, and conference articles that discuss AI techniques such as machine learning, recommendation systems, and real-time feedback. The results show that using AI in online learning platforms can increase student engagement, accelerate feedback, and improve personalization of learning materials. However, there are some challenges when implementing these systems, such as the need for adequate technological infrastructure and teacher training. In conclusion, although AI has a lot of potential to optimize programming learning, effective implementation requires technical and pedagogical considerations. According to this study, further research is needed to overcome implementation barriers and assess the long-term effects of using AI in programming education.

Peningkatan Efisiensi dan Keamanan parkir kendaraan dengan Integrasi KTM berbasis IoT

Fathur Andre Fadilah — 2024-10-23

The research carried out includes analysis of the manual parking system previously used on campus and evaluation of the implementation of an IoT-based parking system with KTM integration. This research aims to solve problems caused by manual systems such as long queues, inaccurate recording and high security risks. By integrating IoT technology, this system is expected to increase work efficiency and parking safety. The research method used is a qualitative approach where information is collected through in-depth interviews, field observations and document analysis. Interviews were conducted with students, administrative staff and parking attendants. Field observations observe directly how this system is implemented and functions in field conditions. Document analysis is used to complement the information obtained from interviews and observations. The data collected shows that the IoT-based parking system with KTM integration significantly reduces the time needed to search for a parking space and speeds up entry and exit from the parking space. Users, including students, administrative staff, and parking attendants, are very positive about the system. They believe this system will facilitate access and increase the efficiency and safety of campus parking. The research results show that the IoT-based parking system with KTM integration has succeeded in increasing operational efficiency and parking safety at Esa Unggul University. The conclusion of this research is that the implementation of an IoT-based parking system integrated with KTM at Esa Unggul University has had a significant positive impact on parking efficiency and safety. The study also identified opportunities for further development, such as integration with digital payment systems and analysis of parking data to improve capacity planning.

Sistem Layanan Pemesanan Kalibrasi Berbasis Web: Studi Kasus PT. Global Quality Indonesia

Catur Muhammad Nugroho — 2024-10-23

Information technology has become an integral part of various aspects of life, including the industrial world. PT. Global Quality Indonesia, a company engaged in calibration services for measuring instruments, is also benefiting from the positive impact of information technology development. PT. GQI has hundreds of customers spread across Indonesia. According to information gathered in 2023, PT. Global Quality Indonesia has provided calibration services for 3,251 orders, calibrating a total of 22,341 instruments. The main challenge faced is the service system which still relies on email for communication and orders. The use of email often results in a backlog of messages that are difficult to respond to promptly, thereby hindering the service process. Additionally, the company's website is not yet optimized to provide information and facilitate orders, limiting customer access to online calibration service bookings. The proposed solution is the development of a web-based ordering system. This will make it easier for customers to place orders and record order data on the website, and for the admin to manage data more efficiently, handling calibration requests, invoices, progress updates, and certificate issuance. This research uses the fishbone method for problem analysis and data collection, followed by system development using the SDLC Waterfall method. Based on the research and implementation, the resulting system can enhance the calibration services at PT. Global Quality Indonesia.

Aplikasi Mobile untuk Manajemen Peminjaman Ruang Kelas Studi Kasus Sekolah Bhineka Tunggal Ika

Nicholas Janitra — 2024-10-23

This research aims to design and implement a mobile application for borrowing rooms and classes at a school called "Sekolah Bhinneka Tunggal Ika". The research methods used include observation and interviews. The research results show that a mobile application-based room lending information system can make borrowing faster and more efficient. This application makes it easier for users to access lending services and helps administrative staff manage loan data in a database and properly record it. In conclusion, implementing the mobile application for borrowing rooms at the Bhinneka Tunggal Ika School succeeded in optimizing the borrowing process, making it faster, more efficient and easier to access for users and helping the school administration manage data.

Desain Dan Implementasi Sistem Informasi Manajemen Presensi PT.XYZ Menggunakan Metode Agile

Jerry Brilianto Akbar — 2024-10-23

This study aims to develop a more efficient and accurate presence management information system at PT Silicaindo. Agile methodology is used to ensure that the developed system is responsive to changes in user needs. The process begins with an in-depth analysis of user needs, which are then implemented into a system design using UML, flowcharts, and wireframes. The developed system is then tested using black-box testing to ensure optimal functionality. After testing, the system is handed over to PT Silicaindo for implementation. User feedback is collected during the review stage, which allows for further system improvements and enhancements. Finally, the system is launched and ready to be used by all employees of PT Silicaindo. This study successfully demonstrates how agile methods can be applied to develop complex and dynamic systems, resulting in systems that are stable, functional, and in accordance with user needs.

Implementasi Artificial Intelligence dalam Meningkatkan Cyber Security: Analisis ancaman dan Pencegahan

Lim Jong Su — 2024-10-23

In today's digital age, cyber threats are becoming more complex and sophisticated.The aim of this study is to analyze the role of artificial intelligence (AI) in improving cybersecurity through threat detection and prevention. By integrating AI techniques such as machine learning and deep learning, cybersecurity systems can detect suspicious behavior patterns and identify threats in real-time.A comprehensive literature review was conducted to explore different AI approaches applied in this field, including anomaly detection analytics, threat intelligence, and automated response. The use of artificial intelligence can significantly improve the accuracy of threat detection and cyber incident response. Moreover, case studies of several organizations that have used AI for cybersecurity have shown increased effectiveness and efficiency in dealing with cyberattacks. However, there are still challenges to overcome, such as: B. Limited training data, interpretability of AI models, and the need for qualified experts. Although AI has great potential to improve cybersecurity, collaboration between technology and human expertise remains crucial to address growing threats.Thus, not only is cybersecurity improving, but there is also an increasing need to develop artificial intelligence (AI) systems that take cybersecurity threats into account in order to attack the security of information systems.

Optimalisasi Fitur Instagram untuk Meningkatkan Kinerja Engagement dan Retensi Pengguna

Fatwa Arriva — 2024-10-24

Instagram has become one of the most popular social media platforms with millions of active users every day. Increasing user engagement and retention is a challenge faced by many companies using this platform. This research aims to identify and optimize Instagram features that can improve user engagement and retention performance. This research adopts a quantitative approach to analyze Instagram usage. Data was collected through an online survey involving respondents from various demographic groups. Statistical analysis was carried out to identify the influence of Instagram features on user engagement and retention. A/B experiments are also conducted to test the effectiveness of certain feature changes in improving platform performance. The research results show that interactive features such as Stories and IGTV have a significant impact on increasing user engagement and retention. Optimizing interactive features on Instagram can substantially improve user engagement and retention performance. This research makes an important contribution in understanding the factors that influence user engagement and retention on social media platforms, especially Instagram, and provides practical recommendations for social media application developers

Efektivitas Zoom sebagai Platform Pembelajaran Hybrid dalam Meningkatkan Partisipasi Mahasiswa

Fatwa Arrevi — 2024-10-24

In the current digital era, hybrid learning has emerged as an effective method in higher education. With the rapid adoption of online learning tools during the COVID-19 pandemic, Zoom has become a popular choice for educational institutions. This study aims to evaluate the effectiveness of Zoom as a hybrid learning platform in increasing student participation. Through a mixed-methods approach, including surveys, interviews, and participation data analysis, we explored how Zoom's features impact student engagement in a hybrid learning environment. Findings indicate that interactive features such as breakout rooms and polling contribute to increased student participation. However, technical issues and digital fatigue remain challenges. This research provides valuable insights for educators and institutions seeking to optimize hybrid learning experiences and enhance student engagement.

Pengembangan website Monitoring Stok Barang Supplier dengan Sistem Rekomendasi menggunakan metode Collaborative Filtering pada Ud. Pekanbaru Jaya

Oddy Virgantara Putra — 2024-10-24

Pekanbaru Jaya, a goods distribution store, frequently faces challenges in monitoring supplier stock and ordering goods, leading to stockouts and operational inefficiencies. This study aims to design and implement an effective and efficient stock monitoring system using the Collaborative Filtering method. This method is chosen for its ability to predict items that users might like based on the opinions of other users, providing accurate recommendations even with limited content information. The system will also employ the Waterfall model in its development, ensuring that each development phase is conducted in a structured and well-documented manner. The implementation of this system is expected to assist UD. Pekanbaru Jaya in managing assets and inventory, ensuring sufficient stock availability, reducing the risk of stockouts, and optimizing resource utilization. The results of this study demonstrate that the developed system can enhance efficiency in stock management and provide a better shopping experience for customers through the online store.

Pemanfaatan Kecerdasan Buatan dalam Pengembangan Pasar E-commerce: Studi Kasus Chatbot dan Penerapan AI dalam Diagnostik Penuaan

Shefia Anggraeni — 2024-10-24

The rapid advancement of technology has led to significant changes across various industry sectors, including e-commerce. The development of artificial intelligence (AI) in e-commerce is one such technology with a substantial impact. This research aims to explain the utilization of AI in e-commerce market development. By understanding how AI can address existing problems and create new opportunities, this study employs a literature review method to examine various relevant research and articles on the application of AI in e-commerce, with a particular focus on chatbots and aging diagnostics. The literature review method was chosen as the primary approach because it allows for the collection and analysis of data from various existing sources, providing a comprehensive overview of current trends and innovations in the field. This research uses a systematic literature review to analyze relevant studies and articles on AI applications in e-commerce, specifically focusing on chatbots and aging diagnostics. The literature review was selected as the main method because it enables the researcher to gather and analyze data from existing academic sources, offering a thorough understanding of current trends and innovations in the field. The research demonstrates that the use of artificial intelligence (AI) in e-commerce has a significant impact on market development and user experience.

Jejak Digital dan Jiwa Remaja: Pengaruh Media Sosial terhadap Kesehatan Mental

Putri Adella Cahyaningtyas — 2024-10-24

In this digital era, social media has become an integral part of everyday life, especially among teenagers. Digital traces left by users on social media cover a wide range of online activities, from uploading photos and videos to interactions with other content. This study highlights how these digital traces can affect the psychological condition of teenagers. Excessive use of social media can cause stress, anxiety, and depression. The pressure to always look perfect, get ‘likes’ and positive comments can cause feelings of insecurity and low self-esteem. In addition, exposure to cyberbullying and negative content also has a negative impact on teenagers’ mental well-being. However, social media also has positive sides, such as increasing social connectedness and providing a platform for self-expression. This article aims to examine various factors that influence adolescent mental health through the use of social media. By understanding the relationship between digital footprints and mental health, it is hoped that effective strategies can be found to minimize the negative impacts and maximize the benefits of using social media. Education about the wise use of social media as well as support from family and the surrounding environment are very important in maintaining the mental health of teenagers in this digital era.

Analisis dampak Teknologi AI terhadap Kualitas dan Aksesibilitas Pendidikan di Era Digital

Anton Nurfendi — 2024-10-25

Education in the digital era faces challenges in enhancing the effectiveness and inclusivity of learning. The use of artificial intelligence (AI) technologies, such as generative tools and ChatGPT, offers innovative solutions to these challenges. This research aims to develop an AI education system that supports personalized learning, automated assessment, and cross-disciplinary applications of ChatGPT. The system development method involves needs analysis, AI system design, and technology implementation in the educational context. The research results show that the system can provide relevant learning experiences by tailoring approaches to individual needs. The practical implication is the adoption of the system by educational institutions to improve the quality and accessibility of digital learning.

Penerapan Algoritma Stemming Nazief-Adriani dengan Metode Cosine Similarity Dalam Aplikasi Ujian Esai

Mohamad Arif Suryawan — 2024-10-25

Essay exam assessment using an exam application takes a long time to check. Answer checking is done by reading carefully. The answers given are some that match the answer key, and some are very different. Therefore, an exam application is needed that can directly assess the essay question answers and then give a score according to the answers written. This study aims to apply the Nazief-Adriani stemming algorithm with the Cosine Similarity method to the high school essay exam application. The research method used in this study consists of two stages, first the Nazief-Adriani algorithm carries out several processes, namely normalizing lowercase letters, punctuation, separating into individual words, removing common words, stemming by removing affixes from root words, mapping synonyms and finally calculating the frequency of word occurrence. Furthermore, the second stage, the Cosine Similarity method is used to compare the level of similarity with the answer key. This study produces an exam application that applies the Nazief-Adriani stemming algorithm in checking essay answers. This exam application is Android-based so that it makes it easier to answer exam questions, the answers are written in the box provided. The essay exam questions that are given are first equipped with the answer key stored in the application. From testing three essay answers, the calculation results using the Cosine Similarity method were obtained, namely: the first answer is 94.3, the second answer is 94.3, and the third answer is 74.5. The first and second answers produce a value of 94.3, indicating a high level of similarity to the answer key. Thus, the application created is expected to make it easier to check answers to essay questions quickly and accurately.

Pengembangan Aplikasi e-Dawlat Ikatan Pesantren Indonesia (IPI) dengan Pendekatan Rational Unified Process

Subandi — 2024-10-25

This research developed the e-Dawlat application, an Android-based mobile platform designed to facilitate the management and mapping of Boarding school, data in the South Kalimantan region. This application aims to improve efficiency and accuracy in disseminating information related to boarding school, to the community. Application development was carried out using PHP in the Laravel framework and Java in Android Studio, with MySQL database support. The Rational Unified Process (RUP) method was used in the development of this application to ensure a structured and iterative process, including system analysis, design, and implementation. The results of this research include the design of six database tables that support various processes in the application, as well as the development of 20 user interfaces to facilitate access to the various menus. The e-Dawlat application was tested using the black-box testing method, which resulted in satisfactory performance. In addition, the usability measurement shows a score of 89.86%, which indicates that this application is very feasible to be used by boarding school, administrators, students, and prospective students. With the ability to display data in real-time and interactively, this application allows quick and easy access to information, anytime and anywhere. The e-Dawlat application is expected to be an innovative solution in supporting the role of the Indonesian Pesantren Association (IPI) South Kalimantan in managing and disseminating information more effectively and responsively to technological developments.

Sistem Dashboard Untuk Visualisasi Data Pendapatan dan Pengeluaran Berbasis Web PT. XYZ

Dwi Rio Aryanto — 2024-10-26

PT XYZ is a finance company engaged in financing. For controling and cost center project management of each branch, financial reports per branch are required. Currently, there is no financial report per branch at PT XYZ, making it difficult for management to determine policies. The company needs a financial data visualization that presents income and expenditure data per branch. To overcome these problems, an effective, attractive, and multifunctional dashboard system is needed. In developing the dashboard system, using the prototype method. To build a dashboard system, python programming is needed for data processing, and apache superset to build interfaces. The result of the dashboard system development is a system that can process data according to logic allocation and display clear and interesting information. This dashboard system has been implemented so that it can help management in analyzing data and making decisions.

Evaluasi Sistem City Dashboard Menggunakan Framework ITIL Versi 3

Alayya Nurin Sani — 2024-10-26

The City Dashboard system is an important tool to fulfill the information needs in the context of smart cities, focusing on six main principles including connectivity, security, energy efficiency, mobility, governance, and environmental sustainability. With the increasing complexity and volume of data that needs to be managed by local governments, the presence of a City Dashboard is becoming increasingly crucial in supporting fast and precise decision-making. However, the City Dashboard System faces several problems that need to be fixed immediately. First, the City Dashboard System is not consistent in presenting data according to the specified time frame to users. In addition, there is no feedback mechanism from users, which hampers the process of improving and developing the dashboard. Finally, there are often page display problems that are under repair, hampering the optimal performance of the system. Immediate improvement efforts are needed to present data consistently, obtain user feedback, and ensure optimal availability of the City Dashboard System. This study aims to conduct an in-depth evaluation of the effectiveness of the City Dashboard system using the ITIL Version 3 framework with the Service Operation domain which focuses on 3 Service Operation sub-domains, namely Event Management, Request Fulfilment, and Incident Management. The evaluation results of the Bekasi City Dashboard System show a maturity level at level 4 (Managed and Measurable) with an average score of 3.50, which means that the maturity level of the City Dashboard System has been implemented as a whole at each layer involved (managers and users) and has been well managed.

User Acceptance Test dan Penerapan Model ADDIE pada Media Pembelajaran Interaktif Pengenalan Profesi

Ari Nurul Alfian — 2024-10-26

Digital technologies such as computers and handheld devices enhance student engagement and motivation and accelerate learning. Vocational introduction subjects are taught using a package book, a minimal tool for explaining the material becomes a reason for introducing interactive learning media for the introduction of various professions in students at Islamic High School Al-Hilal. The learning media development model used is the ADDIE model which includes Analysis, Design, Development, Implementation and Evaluation. The media testing was conducted using Blackbox Testing and User Acceptance Test (UAT). The results of the Blackbox testing were 100% valid and the UAT results were 92% of the applications were highly qualified from the total of 20 respondents. Learning media can help the process of effective learning activities and make it easier for students to understand the introductory material of a variety of professions.

Penerapan Algoritma Apriori Pada Aplikasi Pemesanan Homestay di Desa Marinsow

Ayu Triana Situmorang — 2024-10-26

Marinsow Village is one of the emerging tourist destinations in North Sulawesi, with its main attractions being the natural beauty and authentic local culture. Homestays have become a popular accommodation choice for tourists. This study aims to analyze the booking patterns of homestays in Marinsow Village by applying the Apriori algorithm, which is expected to help improve marketing strategies and optimize homestay booking services. The research method used is the prototype method, along with UML (Unified Modeling Language) to assist in system design. The data used in this study includes homestay bookings from August 2023 to May 2024, with a total of 750 transaction records. The analysis results reveal certain booking patterns that have the potential to be utilized in the development of more targeted promotional strategies and the enhancement of homestay services tailored to tourist preferences.

Pengembangan Aplikasi Youniverse Berbasis Mobile untuk Mendukung Kegiatan Event Komunitas

Chaulina Alfianti Oktavia — 2024-10-26

This research develops the Youniverse mobile application to support community event activities, specifically for the Mobile Class Community of Malang. The application aims to address various issues in event management that are still conducted manually, such as registration difficulties, delays in information dissemination, and data security risks. The research methods include problem identification, problem analysis, data collection through observation, interviews, and questionnaires, as well as literature studies and competitor analysis. The Youniverse application is designed using Dart and Flutter technology for multiplatform compatibility, and Firebase for a secure and scalable backend. The main features of the application include online event registration, real-time notifications, QR code-based check-in, event calendar, ticket management, and feedback collection. The application implementation is carried out with thorough testing to ensure all functions run smoothly. The research results indicate that the Youniverse application successfully improves efficiency, security, and user experience in community event management. This research provides practical contributions to the development of technology to support community activities and offers suggestions for further research in various fields beyond informatics.

Pemilihan Guru Terbaik Berbasiskan Web menggunakan Metode Simple Additive Weighting

Sumardiono — 2024-10-26

The complete information system is technology that is based on the thoughts of people who have interests; the aim is to assist in the activities of these people, especially in an organization such as a school, one of which is selecting the best teachers. We still consider the selection of the best teacher in a school to be subjective, as it involves the appointment of a leader or principal, either without or with the support of objective data. The research is a case study at one of the vocational schools in Bekasi City. This research was carried out using a quantitative approach by developing a web-based system using the Simple Additive Weighting (SAW) method. This SAW method explains values from normalization to preference and ranking, making it easier to determine and select the object in question, namely the best teacher. The results of this research were measured by a usability value of 89%, a reliability value of 88%, an efficiency value of 91%, and a functionality value of 91%. By looking at several system testing factors above, it can be concluded that web-based best teacher selection is ready to be used at the vocational school.

Implementasi Metode Trend Projection pada Sistem Prediksi Penggunaan Consumable Berbasis Web

Dwi Ismiyana Putri — 2024-10-26

Recording the use of consumables in the quality department has not been done consistently and is still done by recording on a piece of paper collection form, then transferring to an excel form, causing errors such as lack of consumable stock before the time the purchase should be made. This causes excess funds and the use of other funds to buy the shortage of consumables needed. This research uses the Extreme Programming (XP) system development model with the Trend Projection method, aiming to overcome existing problems by predicting consumable forecasts based on trends from previous item data. The output of the Trend Projection Method forecasting can help, simplify, and speed up the admin in determining what items are worth buying for use in the next month with a more detailed amount.

Peringkas Teks Otomatis Berita Online Komisi Pemilihan Umum Menggunakan Algoritma K-Means Clustering

Ezra Matthew Warouw Runturamby — 2024-10-26

This research aims to develop an automatic text summarization system capable of summarizing online news about the General Election Commission (KPU) using the K-Means Clustering algorithm. In the current digital era, online news has become a primary source of information for the public, but the overwhelming amount of available information often makes it difficult for readers to filter and comprehend news efficiently. The low reading interest of the public further exacerbates this issue. Therefore, the automatic text summarization system is expected to provide a solution by helping readers quickly and effectively grasp the essence of the news. The K-Means Clustering algorithm will group sentences in the news into several clusters, which will then be used to create a representative summary. This research also identifies challenges such as the accuracy of the summary and the diversity of language in the news. The implementation of this system is expected to improve readers' time efficiency, provide better access to information, and support increased public participation in the democratic process.

Implementasi Augmented Reality untuk Pembelajaran Gerakan Pencak Silat Menggunakan Unity dan Vuforia

Fahmi — 2024-10-26

Pencak Silat is a traditional martial art that originated in Indonesia, now pencak silat is a sport that has many enthusiasts in various countries. At the State Junior High School 4 Wangi - Wangi, pencak silat still uses a learning method with direct practice in the field which is only done 1 time a week. This research aims to design and build a learning application for the Pencak Silat movement by applying Augmented Reality technology. In making this application, there are several stages, namely, character design and animation using avatars sdk and blender which then markers are stored in the Vuforia database and built using unity. This research produces the application of Augmented Reality in Learning Pencak Silat movements as a learning medium that can be used as a learning medium for students, where students can learn Pencak Silat movements by looking at the movements of characters in the application in 3 dimensions so that it will make students enthusiastic in learning Pencak Silat.

Implementasi Projection Profile dan Connected Component untuk Segmentasi Citra Manuskrip Beraksara Jawa Cetak

Gerardus Kristha Bayu Indraputra — 2024-10-26

Javanese script is one of Indonesia's cultural heritages. Many ancient manuscripts in Javanese script are still neatly stored in museums and libraries in Indonesia, but only a few people can utilize the important information contained therein. The difficulty of the transliteration process is one of the challenges in obtaining this important information. With the development of document image analysis science, this research was developed to help shorten the process of transliterating Javanese manuscript images. Segmentation is an essential stage in transliterating the manuscript image, namely, automatically taking each script image in a document. This research developed the segmentation process by combining the projection profile and connected component methods. Using one image from a scanned manuscript in the book "Hamong Tani" written using printed Javanese script on page 5, the results of line segmentation with 100% accuracy and the results of Javanese script segmentation with 95.952% accuracy were obtained after preprocessing. From the large segmentation accuracy value, it can be concluded that the projection profile and connected component methods can be used well in segmenting printed Javanese manuscript images.

Aplikasi Pembelajaran Bahasa Daerah Tontemboan Menggunakan Metode Extreme Programming Berbasis Android

Glendy Koleangan — 2024-10-26

Regional languages play an important role in maintaining the cultural identity of a community, but their use is decreasing due to globalization and technological developments. This study aims to preserve the Tontemboan language, a language used by the Tontemboan tribe in Minahasa, through the development of an Android-based learning application using the Extreme Programming (XP) method. The research method used is application development with data collection methods such as interviews and observations, analysis and qualitative data. The results of the study indicate that this application is effective in improving the understanding and use of the Tontemboan language among users. The conclusion of this study is that technology-based learning applications can be an effective tool in preserving regional languages and cultural heritage.

Implementasi Data Mining Dalam Pengelompokan Data Penyakit Pasien Menggunakan Metode K-Means Clustering

Gusna Mayang Sari — 2024-10-26

This study aims to identify the pattern and distribution of diseases at the Mambi Health Center using the K-Means Clustering method. Patient data includes age, gender, address, and type of disease suffered. This method was chosen because of its ability to group data based on similar characteristics, making it easier to identify dominant diseases. The results reveal the age groups susceptible to certain diseases, the geographical distribution of diseases with high prevalence, and the types of diseases often encountered at the Puskesmas. These insights are expected to help Puskesmas in allocating resources effectively, designing more appropriate prevention programs, and improving the quality of health services. This study also provides recommendations for disease management strategies based on the identified groups, so as to support efforts to improve public health.

Prediksi Pendapatan Penjualan Menggunakan Metode Double Exponential Smoothing Pada Toko Retail XYZ

I Gede Sudiantara — 2024-10-26

Revenue is a key indicator in determining a company's financial success, both for identifying potential profits and losses. This predictive model is designed to assist management in developing strategies to increase product sales. Accurate forecasting can provide early warnings regarding the actions store management needs to take. This study employs the Double Exponential Smoothing Brown method with a smoothing parameter alpha (?) of 0.5. The analysis results indicate that the Mean Absolute Percentage Error (MAPE) values range from 0.26% to 4.29%, demonstrating a high level of accuracy. Based on these MAPE results, the predictive model is then implemented into a web-based system. This system allows management to access information anytime and anywhere. Therefore, this prediction system is expected to assist the store in making strategic decisions, particularly in managing and increasing future revenues

Mapping Review Penerapan Artificial Intelligence pada Cyber Security untuk Meningkatkan Security Awareness

I Putu Agus Eka Pratama — 2024-10-26

The rapid development of information technology (IT), on the one hand, has the potential to increase the number of cyber attacks, so cyber security needs to be handled properly. As the weakest element, efforts are needed to increase cyber security awareness on the user side. Artificial intelligence (AI), which is increasingly developing and widely applied in various fields of life, has the potential to be used to increase security awareness in users. To study this further, a literature study, review, and mapping analysis were conducted from a number of references in order to obtain an overview of the potential and future research plans related to the use of AI in cyber security for security awareness along with providing recommendations. This study conducted a study and analysis using the mapping review method on 37 selected papers indexed by Google Scholar, referring to the NIST (National Institute of Standards and Technology) framework. The results of the mapping review show that the mapping of publications related to the application of AI to cyber security to increase security awareness is the most in 2024, with the most trends being education/training, and the most widely used AI method is deep learning. This study recommends education and deep learning as areas that can be taken for future research related to the application of AI to cyber security.

Klasifikasi Daun Kelor Kering Berbasis Vision Artificial Intelegence

I Wayan Sudiarsa — 2024-10-26

The drying process of moringa leaves (Moringa oleifera) is necessary to reduce the moisture content so that the leaves become dry and can be utilized for the next processes. Drying moringa leaves to change the moisture content from 80% to 9.2% requires an ideal heating condition, as the heating rate must not damage the nutritional content present in the leaves. The utilization of ANN models can recognize seasonal time series data patterns. The introduction is categorized into several classifications. By using IoT, it is hoped that the drying conditions can be monitored. The system is also connected to a recommendation system using Recurrent Neural Networks (RNN), which will provide recommendations for the best conditions for moringa flour production. The Google Cloud Vision AI system suite combines artificial intelligence with other technologies to understand and analyze videos and easily integrate vision detection features into applications. These tools are available through APIs and can still be customized for specific needs. The Google Cloud Vision AI system suite combines artificial intelligence with other technologies to understand and analyze videos, as well as to easily integrate vision detection features into applications. These features include image labelling, face and structure detection, optical character recognition (OCR), and tagging of vulgar content. The test results found that the Vision AI system used has been tested to detect and classify moringa leaves, both in wet and dry conditions. The testing was conducted using a mobile-based Vision AI application and the Google Cloud Vision API. The results indicate that the system detects moringa leaves more as a plant.

Perancangan Aplikasi Simpan Pinjam dengan Gamifikasi untuk Peningkataan Partisipasi Anggota Koperasi Simpan Pinjam

Ilham Adi Maulana — 2024-10-26

Savings and loan cooperatives are financial institutions owned and operated by their members to provide savings and loan services for their economic welfare. This research aims to design a web-based application with a gamification model at the Usaha Mandiri Savings and Loans Cooperative. This model is expected to increase member involvement and cooperative growth through technological innovation. It is hoped that the application of this gamification will maintain the relevance of cooperatives in the digital era, as well as encourage members' active participation in cooperative activities. This research not only provides insight into the application of gamification in a cooperative context but also practical guidance for application developers to increase member participation and organizational growth. In addition, this research serves as inspiration for the development of technology and innovation in the cooperative sector. With this gamification model, cooperatives are expected to be able to adapt to the challenges of the digital era and continue to provide greater benefits for their members and the wider community.

Implementasi Algoritma ECLAT dalam Menemukan Pola Asosiasi Antar Produk Pada Perusahaan Retail

I Made Dwi Putra Asana — 2024-10-26

Toko XYZ, a retail company in Denpasar, faces challenges in managing its product stock due to the lack of utilization of consumer purchasing patterns in product placement and inventory management. As a result, products that are frequently bought together by customers often run out of stock, leading to potential sales declines. To address this issue, a purchasing pattern analysis was conducted using the association rules method with the ECLAT algorithm. The analysis was performed using Visual Studio Code with Python programming language to identify frequent 1-itemsets and frequent 2-itemsets, which represent products frequently purchased individually or in combination by customers. The analysis results show that lower minimum support values result in more frequent item sets being identified while increasing the minimum confidence, which narrows the number of generated association rules. At a minimum support of 0.05, 2463 rules were identified, whereas at a minimum support of 0.20, the number of rules decreased to 117. Higher minimum confidence, set at 60%, produced more relevant and reliable rules, demonstrating the potential of the ECLAT algorithm in aiding inventory management and optimizing product placement at Toko XYZ.

Analisis Efektivitas Aplikasi ‘Super Apps’ dalam Proses Pendaftaran Turnamen Olahraga di KONI Kabupaten Tangerang

Irsyad Taufiq Ilham Supardi — 2024-10-26

This study aims to evaluate the effectiveness of the "Super Appsb " application in facilitating the registration process for prospective participants in sports tournaments organized by KONI Kabupaten Tangerang. The application is designed to address various obstacles in manual registration, such as time constraints, data input errors, and slow processes. The evaluation is conducted using quantitative methods to measure user satisfaction, system effectiveness, and the application's impact on the number of registrants and the time required to complete the registration process. Data is collected through surveys involving 200 prospective participants who have used the application to register for sports tournaments. Quantitative data analysis is performed using descriptive statistics and regression tests to examine the relationship between the application's ease of use and levels of satisfaction and registration effectiveness. The results indicate that the "Super Apps" application significantly simplifies the registration process, reduces data errors, and accelerates registration time. User satisfaction is also high, with the majority of respondents stating that the application is more efficient compared to manual registration methods. This study provides recommendations for further development of the application in terms of user interface and the integration of additional features that can enhance user experience

Pengembangan Game Edukasi Pengenalan Hutan Bakau Mangrove Ngurah Rai Berbasis Android

Kadek Surya Adi Saputra — 2024-10-26

Mangrove forests in Ngurah Rai have a very important ecological role, but public awareness of their existence and benefits is still low. This research aims to develop an android-based educational game that introduces mangrove forests to the community, especially the younger generation and tourists. The method used in this educational game application is waterfall or called system development life cycle (SDLC). This application testing stage uses the white box testing method with the base path technique of calculating the number of scenarios carried out by the user and black box testing for application functionality testing. It is hoped that this educational game can be an interesting tool to support environmental conservation efforts and increase community involvement in mangrove forest conservation and also contribute to the development of innovative learning media that integrate technology and environmental education

Perancangan Knowledge Management System Kegiatan Karyawan Berbasis Android

Khairunisa Nabila Salamah Ongso — 2024-10-26

Museum is an institution that functions to protect, develop, utilize collections, and communicate them to the public. To carry out these functions properly, all employees in the Museum unit must be aware of all existing activity information. Problems experienced in the internal environment of employees at the Museum are in the form of activity information management and dissemination. The delivery of activity information for some employees still uses manual methods, such as writing on the blackboard, communicating verbally, and using google docs. As well as information sources that are not centralized in one source can hinder the change of tacit knowledge to explicit, limiting the accessibility and mobility of existing information. Therefore, this research aims to design a Knowledge Management System application for internal employee activities based on android to overcome these obstacles. A solution is proposed to help employees get the latest information quickly and efficiently. The information system was developed using the User Centered Design method which enables a development process that focuses on the end user. The results of this application research get 85% overall in the test, so this Knowledge Management System application can make a positive contribution to employee productivity and collaboration and advance service quality in the museum work environment.

Mengenal Model BERT dan Implementasinya untuk Analisis Sentimen Ulasan Game

M. Fadhilatur Ramadhan — 2024-10-27

This Systematic Literature Review (SLR) analyzes the use of the BERT (Bidirectional Encoder Representations from Transformers) model for sentiment analysis of game reviews. The research identifies methods of implementing BERT, evaluates its effectiveness compared to other models, and explores challenges and opportunities in this context. Results show that BERT consistently outperforms traditional models, with an average accuracy improvement of 3-7%. BERT architecture variations, adiptive fine-tuning techniques, and pre-processing specific to game languages proved effective. Practical applications include game sales prediction and identification of preferred features. Key challenges include high computational requirements and handling game-specific context. Future research directions include domain-specific model development, multi-modal integration, and improved interpretability. This SLR provides a foundation for further research in the use of advanced language models for sentiment analysis of game reviews.

Pengembangan Dan Evaluasi Aplikasi Mobile Untuk Meningkatkan Efisiensi Pelaporan Data on Shelf Availability (OSA)

Dimas Surya Dilana — 2024-10-27

Technological developments in industry FMCG gave rise to the need to develop a data reporting system OSA that is effective and efficient. FMCG is an industry that provides daily needs for consumers. In industry FMCG there is a problem in data reporting OSA i.e. it takes 2 hours to match the product barcode This resulted in field officers not being able to meet the target stores they had to visit. The research methodology used in this research is a system-based development agile method. First, identify problems in data reporting OSA then determine the programming language to be used and design user interface. After requirement and design If you're ready, then move on to develop by changing the display design user interface into a programming language so that it can be used. The last one was testing with the aim of whether the design can help users and is ready for use, after the product passes the testing stage the application is ready to be distributed widely. Results of development and evaluation of data reporting applications OSA can increase the efficiency of data reporting OSA so that field officers can meet shop visit targets.

Perancangan Sistem Pengaduan Masyarakat untuk Mempermudah Pelaporan Permasalahan Lingkungan Warga Pademangan Barat Jakarta Utara

Muhammad Kaisar Stevan Priadi — 2024-10-27

Environmental problems in RT 16/RW 07, West Pademangan Village, North Jakarta, often require fast and precise handling. However, an unstructured manual reporting process hampers the communication of citizen complaints to the authorities. To overcome this, this research aims to design and develop a web-based public complaint system that makes it easier to report environmental problems. This system was developed using the prototyping method, which allows iterative development based on input from users. With this approach, the system can be more easily adapted to the needs of residents and local officials. The development process includes needs analysis, user interface design, and repeated testing of system functionality to ensure effectiveness and efficiency in delivering reports. The results of this research show that a web-based complaint system is able to increase citizen participation in reporting environmental problems and speed up the follow-up process from local authorities. This system is expected to be an efficient solution and can be implemented on a wider scale.

Evaluasi Learning Management System Pada E-Campus Menggunakan End User Computing Satisfaction Di Universitas Bina Insani

Stepphanus Manurung — 2024-10-27

E-Campus is a complete web-based (enterprise) application that helps manage/administrate academic activities at an institution of higher education (University, College, Institute, Polytechnic, Academy, etc.). The management in question includes data collection (new students, lecturers, faculties, study programs, courses, curriculum, etc.), scheduling lectures, teaching and learning activities (attendance, material delivery, quiz, UAS, UTS, etc.), to data reporting. The features of the ecampus are still not felt by students in their use. This evaluation uses the EUCS (End User Computing Satisfaction) method which uses 5 dimensions, namely; Content, Accuracy, Format, Ease Of Use, Timeliness. The population in this study were actived users members, namely Bina Insani University students with a total sample size of 96 respondents. The media for distributing questionnaires is using google forms which are distributed via whatsapp and instagram as well as directly to activated users. The analysis method used is SEM (Structural Equation Modeling) with the Partial Least Square (PLS) Method. The calculation tool used is SmartPLS 3 student version. The result of this analysis is the acceptance of the five hypotheses tested. So that these results indicate that Ease Of Use and Timeliness are proven to have a positive and significant effect on the use of User Satisfaction. This Ease Of Use test value is evidenced by a path coefficient value of 0.32 and a t-statistic value of 2.605. Timeliness is proven to have a positive and significant effect on User Satisfaction. This is evidenced by the path coefficient value of 0.29 and the T-Statistic value of 2.519. While the Content, Ease Of Use, Format variables do not provide significant results on user satisfaction.

Implementasi Media Interaktif Tableau Untuk Pengembangan Visualisasi Data ASN Menggunakan Metode ETL

Nikhlatul Maolah — 2024-10-27

The State Civil Apparatus is a profession for Civil Servants (PNS) and government employees with work agreements who serve government agencies who are appointed by civil service development officials and entrusted with other state duties and are paid based on statutory regulations and provide professional and quality public services. However, the large amount of data from the number of State Civil Apparatus in the Cirebon district government office makes it difficult for decision-makers to understand and analyze the data. This study aims to develop data visualization for State Civil Apparatus (ASN) in sub-district offices through the application of interactive media Tableau using the ETL (Extract, Transform, Load) method. The extract stage is the data collection stage from the Cirebon district communications and information services office in the form of State Civil Apparatus (ASN) data, spatial group, education, age and religion. Transform is the process of changing data from a previous format to the desired format. At this stage, the data relationship process is carried out to adjust several types of variables. Load is the final process that functions to enter the data into the final target, namely into the Source data in Tableau. The aim of this research is to design ASN data visualization using the interactive media Tableau. Data visualization displays some visual data in the form of bar graphs. With the availability of information in data visualization, it can make it easier for stakeholders to make decisions. In this era of digitalization, the need for efficient and transparent data processing has become very important, especially in government agencies. Utilizing Tableau as an interactive data visualization tool and exploring a more informative dashboard presentation

Aplikasi Citra Digital untuk Klasifikasi Kematangan Buah Pepaya

Ulfa Laela R — 2024-10-27

There are still many people who use the manual system by looking directly at or guessing the maturity level of papaya fruits, with classification results that are less than optimal. The purpose of this study is to design a digital image application that can be useful in distinguishing the ripeness of naturally ripe papaya fruits and carbites. This application uses 2 extraction features, namely texture and colour, for texture uses Grey Level Cooccurence Matrks (GLCM), while colour uses Hue, Saturation, Value (HSV) and K-Nearest Neighbour (K-NN) algorithm to classify. The result of this study is the creation of a digital image application, which can help distinguish the ripeness of papaya fruit from the results of the classification of natural ripe and ripe carbine. Based on the test results, 60 training data and 15 testing data were used. By producing an accuracy value of 80% on each testing data that has been carried out.

Studi Implementasi Aplikasi Keuangan Android dengan Analisis Data

Rizki Dwi Sanjaya — 2024-10-27

In this modern era, efficient personal financial management tools are increasingly needed. Applications for Android-based mobile phones offer an efficient and easy-to-use method of managing personal finances. The aim of this research is to create and implement a personal financial management application that has data analysis features that help people manage income, expenses and savings. The app has features such as transaction recording, financial reporting, and data analysis, which provides information on spending patterns and recommendations for reducing costs. This study uses user interface design, application development using Android Studio, and application testing with end users. Studies show that these apps can help people make better financial decisions and better understand their financial condition. This research helps develop mobile applications by including data analysis features that help users manage finances.

Prototipe Kelas Pintar Berbasis Android Menggunakan Metode Rapid Application Development Di Universitas Bina Insani

Tiar Permana — 2024-10-27

The concept of smart classrooms has become a solution to improve the efficiency of the teaching and learning process. However, there are still challenges related to classroom preparation and management, such as forgetting to turn off devices after use or leaving the room without locking the door. The aim of this research is to develop the BiU-Class application to remotely control devices in the classroom. The development method used is Rapid Application Development (RAD) to accelerate the development process. Testing results between the application and the devices show that the system works well, demonstrating that the Smart Classroom concept has the potential to address problems in education. However, its implementation is currently hindered by electrical issues that require further research. The developed application is considered easy to understand by users, thus having the potential for future development and use once technical issues are resolved.

Analisis Kelayakan Peminjaman Uang untuk Pembelian Properti Dipengaruhi oleh Status Perkawinan dan Jumlah Tanggungan Menggunakan Algoritma Naïve Bayes

Sri Erina Damayanti — 2024-10-28

This study aims to analyse the feasibility of loan approval for property purchases influenced by marital status and the number of dependents using the Naïve Bayes algorithm. Data were collected from a bank and analyzed using Orange Data Mining software. The results show that the Naïve Bayes algorithm is effective in predicting loan feasibility with an accuracy rate of 80.4%. Other evaluation metrics such as F1 score, precision, and recall also demonstrate good performance, with values of 78.2%, 81.4%, and 80.4% respectively. Although there are some weaknesses in predicting both positive and negative classes with equal accuracy, overall, the Naïve Bayes method remains reliable for this purpose. The implementation of this algorithm using the Orange Data Mining toolkit facilitates the data analysis and visualisation process, providing a clear understanding of the factors influencing loan feasibility for borrowers.

Analisis Bibliometrik: Pemetaan Penelitian Machine Learning dalam E-commerce Berdasarkan Data dari Scopus (2019-2024)

Yudhistira Arie Wijaya — 2024-10-28

This study explores the application of machine learning in e-commerce using descriptive and visual bibliometric analysis methods. Data were collected from the Scopus database for the period 2019–2024 through five stages: defining search keywords, initial search results, refinement of the search results, compiling statistics on the initial data, and data analysis. The findings indicate a significant increase in publications from 2020 to 2023, peaking in 2023, followed by a decline in 2024. IEEE Access and the International Journal of Advanced Computer Science and Applications are the main sources of publications, with India and China standing out as the countries with the highest number of publications. International research collaboration shows significant growth, and co-word analysis identifies “machine learning” as a central topic closely linked with “electronic commerce” and “learning systems." Citation trends reveal that highly cited publications have a significant impact. These findings provide comprehensive insights into the development and contributions of research in machine learning for e-commerce, with important implications for researchers and industry practitioners in addressing new challenges and opportunities.

Studi Bibliometrik Implementasi Teknik Machine learning dalam Bidang Customer Relationship Management

Khaerul Anam — 2024-10-28

Application of machine learning techniques in Customer Relationship Management has proven to have significant potential in enhancing the efficiency and effectiveness of managing customer interactions. This study aims to conduct a comprehensive bibliometric analysis regarding the application of machine learning techniques in CRM. Through this analysis, we seek to identify recent research trends, gaps, and future research opportunities. This study utilizes data from various prestigious international scientific journals indexed by Scopus to explore the application of machine learning techniques for churn prediction models. The method employed in this research is bibliometric analysis on machine learning techniques in the field of CRM. This study reveals a significant trend in the application of machine learning techniques in Customer Relationship Management. The results indicate that the use of machine learning in CRM has increased, particularly since 2021, reflecting a high interest and the relevance of this technology in enhancing the efficiency and effectiveness of CRM. The analysis also shows that the discipline of computer science dominates this research, followed by engineering, business and management, and mathematics. The contribution of this research to existing knowledge is providing a deeper understanding of current research trends and identifying gaps and future research opportunities.

Bibliometric Analysis Impact of Machine Learning on Mental Health in Student Learning

Fadhil Muhammad Basysyar — 2024-10-28

The integration of machine learning in educational settings offers promising avenues for addressing mental health challenges among students [1]. This study conducts a bibliometric analysis to explore the impact of machine learning on mental health within student learning environments. By systematically reviewing peer-reviewed articles, conference papers, and relevant literature from the past decade, this research identifies key trends, challenges, and opportunities in this emerging field. The study focuses on the effectiveness of different machine learning methodologies in detecting, diagnosing, and intervening in mental health issues, highlighting the potential for early identification and personalized support. Furthermore, it addresses critical concerns related to data privacy, ethical considerations, and algorithmic biases, which are paramount for the responsible deployment of these technologies. The findings reveal significant advancements in the application of natural language processing and wearable technology data for mental health monitoring. However, gaps remain in longitudinal studies and the consideration of cultural and contextual factors. This research contributes to the existing body of knowledge by providing a comprehensive overview and identifying directions for future research, ultimately aiming to enhance the well-being and academic performance of students through innovative machine learning solutions.

Bibliometrik Analisis: Teknologi Permainan Bidang Pendidikan Pada Sekolah Menengah Pertama

Rudi Kurniawan — 2024-10-28

This study explores the use of game technology to enhance learning motivation and engagement among junior high school students in Indonesia. The background of the problem indicates low levels of learning motivation and student engagement in conventional learning processes. The root of this problem is linked to traditional teaching methods that are less engaging for students. This study aims to evaluate the effectiveness of game technology in addressing this issue. The research method employed a mixed methods approach involving a literature review, the development of educational game modules, and case studies in several junior high schools in Indonesia. The data used includes surveys on students' learning motivation, observations of student engagement, and interviews with teachers. The study also collected qualitative data from students' firsthand experiences in using game technology in learning. The results of the study demonstrate that the integration of game technology into the junior high school curriculum significantly increases students' learning motivation and engagement. Students who used educational games showed increased interest in the subject matter, were more active in class participation, and had a better understanding of the concepts taught. This study concludes that game technology is an effective tool for improving the quality of education in junior high schools and recommends a broader adoption of this technology in the Indonesian education system.

Bibliometrik Analysis: Konten Video Untuk Meningkatkan Daya Tarik Pariwisata

Arif Rinaldi Dikananda — 2024-10-28

The use of video content as a marketing tool in the tourism industry has seen a significant increase in recent years. This research aims to explore and develop effective video content strategies in increasing tourism appeal and influencing tourists' decisions to visit certain destinations. Research methods include bibliometric analysis of video content used in tourism marketing, as well as experiments to test the effectiveness of various video content strategies. The results of the study show that the characteristics of travel vlogs that include personal narratives, attractive visuals, and relevant information can increase user travel intentions. Additionally, audience engagement through short videos has proven to be a key factor in increasing travel interest. This research makes a new contribution in understanding the role of video content in tourism marketing and developing a video marketing strategy model that can be applied by the tourism industry to increase the attractiveness of tourist destinations. By utilizing the results of this study, the tourism industry can optimize the use of video content to reach a wider audience and increase positive perceptions of tourist destinations.

Analisis Bibliometrik: Media Pembelajaran Interaktif di Bidang Teknologi Pendidikan pada Database Scopus Tahun 2018-2024

Fatihanursari Dikananda — 2024-10-28

This study aims to analyze the trends in the use of interactive learning media in the field of educational technology through a bibliometric approach. Interactive learning media encourage active engagement of learners and include mobile apps, interactive whiteboards and interactive videos. Studies show that interactive media improve students' motivation, learning outcomes and creative thinking skills. Bibliometric methods were used to explore and visualize research trends and collaborations between researchers and institutions in this field. Data was collected from academic databases that included scientific articles, conference proceedings and dissertations. Tools such as VOSviewer were used to map collaboration networks and keyword trends that revealed several key research themes, including the effectiveness of interactive learning media, the development of technology-based media, and their implementation in various educational contexts. This study provides an in-depth understanding of research developments in interactive learning media and identifies research gaps that could be a focus in the future. The results show a significant increase in the number of publications related to interactive learning media in recent years. The study also identifies key centers of research excellence and collaborations between institutions.

Systematic Bibliometric Research Trend of Text Mining on Product Comments in Business Ecosystem

Gifthera Dwilestari — 2024-10-28

The business ecosystem represents a new paradigm that has gained considerable attention among researchers and practitioners. Despite its popularity, systematic literature reviews utilizing bibliometric analysis within this context remain sparse. This study aims to conduct a comprehensive bibliometric and visualization analysis of business ecosystem research, focusing on the impact of text mining on product comments. Employing VOSviewer for visualization, the study evaluates 95 scientific articles indexed in Scopus quartiles Q1 to Q4 from the Scopus database over the last decade (2001-2024). The bibliometric analysis identifies the most productive publishers, the evolution of scientific articles, and citation patterns. Visualization with VOSviewer reveals prevalent terms in titles and abstracts, author collaboration networks, and assists in identifying novel and underexplored topics within the business ecosystem. The findings provide valuable insights for researchers and practitioners, highlighting key trends and potential research gaps, thus contributing to the advancement of knowledge in the field.

Bibliometrik Analisis: Brand Awareness Program Studi Diploma 3 Pada Database Scopus

Bani Nurhakim — 2024-10-28

This research aims to analyze the factors influencing brand awareness in the Diploma 3 program and to develop effective marketing strategies to enhance that awareness. The background of this study is based on the importance of brand awareness in influencing prospective students' decisions and public perception of the quality and reputation of educational institutions. This research employs survey and interview methods involving students, prospective students, and marketing staff from several higher education institutions in Indonesia. The data obtained were analyzed using statistical methods to identify the main factors affecting brand awareness. The results indicate that digital marketing and social media marketing play a significant role in increasing brand awareness of the Diploma 3 program. Consistent, innovative, and effective marketing strategies through social media have been proven to enhance recognition and appeal of the study program in the eyes of prospective students. This research makes an important contribution to the development of educational marketing strategies and offers new approaches to enhancing brand awareness of the Diploma 3 program. Thus, the results of this study are expected to assist educational institutions in increasing enrollment and retaining students by improving effective brand awareness

Bibliometric Analysis: Machine Learning untuk Blended Learning

Agus Bahtiar — 2024-10-28

Blended learning, which combines face-to-face learning methods with digital technology, has grown rapidly thanks to advances in information technology. Along with that, machine learning technology offers great potential to improve personalization and adaptation in blended learning. This research aims to explore the application of machine learning in blended learning systems through bibliometric analysis. By analyzing SCOPUS indexed publications from 2019 to 2024, this study identifies trends, challenges and opportunities in the integration of machine learning with blended learning. The methods used include search keyword definition, initial data collection, refinement of search results, statistical compilation, and data analysis. The main findings show that there is a significant increase in the number of publications on this topic, with the highest peak in 2022. The wide distribution of publications indicates significant international collaboration. Citation analysis indicates that the quality and impact of research is also increasing, with recent publications gaining more citations. This research highlights the importance of applying machine learning in blended learning to improve educational effectiveness and support the development of more adaptive learning methods. The findings provide valuable insights for academics and practitioners to encourage further innovation and improve the quality of education in the digital era.

Bibliometrik Analysis: Signal Preprocessing Techniques for Kualitas Sinyal Electrogram

Odi Nurdiawan — 2024-10-28

This study explores electroencephalogram (EEG) signal preprocessing techniques used in the early detection and diagnosis of epilepsy, aiming to enhance the quality and reliability of data used in clinical applications. Effective signal preprocessing techniques are crucial for minimizing artifacts and noise, which can obscure critical information in EEG signals. More accurate EEG signal processing allows for the identification of abnormal patterns associated with various neurological conditions, such as epilepsy, which heavily relies on this signal analysis for precise diagnosis. This study conducted a bibliometric analysis using a descriptive approach to identify research trends, geographic distribution, institutional contributions, and key authors in this field. Data was collected from the Scopus database using the keywords "electroencephalogram AND signal AND processing AND epilepsy". The analysis results show a significant increase in the number of publications related to EEG signal preprocessing techniques over the past five years, with major contributions from countries like China, India, and the United States, reflecting the high global interest and focus on this topic. Additionally, deep learning and machine learning techniques emerged as the most dominant methods in this research, indicating future trends in the development of increasingly sophisticated EEG signal processing technologies. The findings also suggest that using techniques such as artificial neural networks, convolutional neural networks (CNN), and deep learning can enhance the accuracy of epilepsy diagnosis and prediction, making a significant contribution to modern clinical practice. Moreover, this study emphasizes the importance of developing and integrating more advanced preprocessing techniques to improve the effectiveness of EEG signal detection and classification, which is expected to enhance diagnostic outcomes and patient management with neurological disorders. This study provides valuable contributions to the development of medical diagnostic technologies, particularly for neurological disorders such as epilepsy, and highlights the need for further research to optimize these techniques for broader clinical application.

Analisis Internet Network Performance Menggunakan Parameter Quality of Service Pada Jaringan STMIK IKMI Cirebon

Martanto — 2024-10-28

The use of the internet for employees is a crucial need to support the completion of their work. STMIK IKMI Cirebon also provides internet facilities for its employees. However, the internet facilities provided are not yet optimal, as evidenced by frequent connection disruptions. This study aims to measure the performance of the internet connection at STMIK IKMI Cirebon. The method used is Quality of Service (QoS), which is a method to assess how well the installed network functions and its ability to define the attributes of the network services provided. QoS is necessary to calculate the parameters that determine the quality of an internet network. The steps in this study include recording network traffic using Wireshark, followed by calculating parameters such as bandwidth, packet loss, delay, throughput, and jitter. The study results indicate that during data upload from 08:00 to 12:05 at STMIK IKMI Cirebon, the throughput percentage achieved was 31% with an index of 1 "POOR," delay was 9.444 ms with an index of 4 "VERY GOOD," jitter was 8.444 ms with an index of 3 "GOOD," and packet loss was 0% with an index of 4 "VERY GOOD." During data download from 15:00 to 19:05, the throughput percentage achieved was 132% with an index of 4 "VERY GOOD," delay was 14.052 ms with an index of 4 "VERY GOOD," jitter was 13.052 ms with an index of 3 "GOOD," and packet loss received an index of 4 "VERY GOOD." Based on these results, it can be concluded that these values have met the TIPHON standard for both upload and download, indicating that the internet connection at STMIK IKMI Cirebon is still suitable for use

Bibliometrik Analysis: Kontruksi Sosial Masyarakat Mengenai Teknologi AI Pada Data Base Scoupus 2014-2024

Nisa Dienwati Nuris — 2024-10-29

This research investigates the social construction of ChatGPT technology in society by identifying and analyzing the factors that influence its adoption and utilization. Through this analysis, we aim to identify recent research trends, gaps, and future research opportunities. The study utilizes data from various international scientific journals indexed by Scopus to explore the application of social construction of technology techniques and their societal impact. The method used in this research is bibliometric analysis to uncover patterns in the study of the social construction of ChatGPT technology in society. The results show that user perceptions of ChatGPT are influenced by digital readiness, technological literacy, as well as perceptions of benefits and risks. Additionally, ChatGPT is closely related to the development of critical skills among students, supporting the enhancement of analytical and critical abilities. The research focus in the field of AI, particularly concerning social and economic impacts, is expanding. This study emphasizes the importance of AI in various aspects of life and its contribution to sustainable development, especially in higher education, where AI technology integration is involved. Educational institutions are encouraged to design policies to support learning and skill development through AI. This research has limitations, particularly in terms of sample size and methodology, which can be addressed in future studies by expanding the scope and methods of the research. Overall, this study enriches the understanding of the impact of AI technology, particularly ChatGPT, in higher education and provides a foundation for further research.

Bibliometrik Analysis: Pembelajaran Speaking Session Menggunakan Instagram Pada Data Base Scopus 2014-2024

Riri Narasati — 2024-10-29

In today's digital age, social media plays an important role in various aspects of life, including education. This research explores the use of Instagram as a learning tool to improve English speaking skills. Through bibliometric analysis, this study identifies previous research trends and evaluates the effectiveness of Instagram-based learning methods. It also reviews existing literature to understand how Instagram has been used in language learning contexts, as well as identifying existing research gaps. The results show that the use of Instagram in English language learning can increase student motivation and participation. Interaction through video, story and dialog-based content on Instagram proved effective in improving speaking skills. The study also found that the use of project-based tasks on Instagram can help students in developing their confidence and speaking ability. In addition, this study highlights the importance of structured guidance and feedback in maximizing the benefits of learning through Instagram. This research makes a novel contribution to the literature by offering a more in-depth approach to the use of Instagram in English language learning. By exploring effective learning strategies and their impact on students' speaking skills, this study explores the role of Instagram in English language learning.

Bibliometrik Analysis: Optimasi Regresi Linear untuk Estimasi Big Data pada Database Scopus Tahun 2013-2024

Ahmad Faqih — 2024-10-29

This bibliometric analysis investigates the optimization of linear regression for big data estimation, focusing on publication trends, citation metrics, geographic distribution, and research innovations from 2013 to 2024. The publication trend analysis reveals a significant increase in research on linear regression optimization, peaking in 2023, followed by a decline in 2024. Citation analysis shows that although this topic is relatively new, it has gained increasing scientific recognition, indicating its growing relevance. The geographic distribution highlights China, the United States, and the United Kingdom as the leading contributors to research on linear regression optimization for big data. Key innovations in this field include the application of quantum algorithms and advanced optimization techniques, which have significantly improved computational efficiency and the accuracy of linear regression models in handling large and complex datasets. These findings underscore that linear regression optimization will continue to evolve and make important contributions to big data analytics.

Analisa Pengaruh Jumlah Penerima dan Penyaluran Pinjaman melalui Finansial Teknologi (fintech) terhadap Pertumbuhan Ekonomi Masyarakat melalui Regresi Linear

Sri Farida Utami — 2024-10-29

This study looks into the relationship between the number of loans received and the amount funnelled by the technology financial platform and the economic growth of a population. Fintech. The method used in this study is linear regression. In recent years, fintech has grown to be a significant component of the financial system, particularly in emerging nations like Indonesia where traditional financial services are still unavailable. The study begins with the hypothesis that fintech can improve financial inclusion; theoretically, this will raise economic growth by improving the distribution of financial resources and the ease with which credit can be obtained. Important variables that were examined in the study were the total number of borrowers, the distribution of loans overall, and measures of economic growth. The outcomes of the linear regression demonstrated a strong positive association between the quantity of borrowing, the availability of fintech loans, and the population's economic expansion. The report emphasizes the significance of rules that enable healthy and inclusive fintech growth and offers pertinent policy implications for decision-makers and players in the fintech industry. The study's finding supports the claim that, by facilitating better access to credit and a more fair distribution of credit, fintech may significantly contribute to economic growth. According to the report, in order to maximize fintech's beneficial effects on the economy, policies that foster its growth are necessary.

Implementasi Algoritma Fisher Yates Pada Media Pembelajaran Aksara Lontara Berbasis Augmented reality

Mirfan — 2024-11-28

The teaching and learning process carried out using the lecture method without the support of learning media, will result in students getting bored so that students do not have the enthusiasm to learn. Meanwhile, the impact when the questions are not randomized in the learning media causes monotonous learning so that students will face the same sequence of questions every time. they learn, causing boredom and reducing interest and involvement in the learning process. Increased Memorization Without Understanding: Users may only memorize the sequence and answers to questions without truly understanding the material, reducing the effectiveness of learning and in-depth understanding of concepts. This research aims to Design Literacy Learning Media Lontara Based on Augmented Reality and Implementing the Fisher-Yates Algorithm Lontara Script Learning Media Based on Android Augmented Reality. The research design used is Unified Modeling Language (UML) which is designed in a structured manner consisting of use case diagram model designs, activity diagrams, sequence diagrams and class diagrams, software applications using Unity, Vuforia using the Fisher-Yates Algorithm. Results of the research This is the Fisher-Yates algorithm ensuring the order of the questions is always random every time it is run. This makes the user's learning experience more dynamic and interesting. This algorithm is very effective in creating variations in the presentation of questions

Kombinasi Algoritma KNN, HSV dan LBP Pada Pengolahan Citra Digital untuk Membedakan Kematangan Pisang

Mirfan — 2024-11-29

The use of carbide in ripening bananas can result in chemical contamination of bananas. This can have a negative impact on the health of consumers who consume these bananas, so this research aims to design a system to differentiate between naturally ripe bananas and carbonated ripe bananas with Digital Images using the Hue Saturation Value (HSV), Local Binary Patterns (LBP) and K-Nearest Neighbor (K-NN). In this research, the system development used is UML (Unified Modeling Language). Meanwhile, making software in this system uses PHP, HTML, CSS, Java script software and for the database uses MySql. This research collects data obtained through observation, interviews and literature study. The method used to create this system is Hue Saturation Value (HSV) to extract color features, Local Binary Patterns (LBP) to extract texture features and the K-Nearest Neighbor (K) algorithm. -NN) for classification of plantain types. The digital image classification system distinguishes naturally ripe or carbitant plantains and can display classification results well so that it can help the public in distinguishing naturally ripened bananas or carbitants. The system created has been able to implement the Hue Saturation Value (HSV), Local Binary Patterns (LBP), and K-Nearest Neighbor (KNN) methods well and the system can differentiate naturally ripe bananas and carbonates well with a level of accuracy for the k= value 3, namely 100%, k=5 96.67%, k=7 93.33% and k=9 with an accuracy of 96.67% from 30 testing data using 200 training data.

Implementasi Retrieval Augmented Generation untuk Layanan Informasi Kampus dengan Chatbot Berbasis AI

Yoni Tribber — 2024-11-30

Information technology plays a crucial role in enhancing knowledge and awareness, particularly in educational institutions with intense competition among universities. Students and the general public still face difficulties in obtaining the necessary information due to the numerous available platforms and the lack of effective search features. This research aims to develop an AI-based chatbot, specifically using Large Language Models (LLM), that can offer efficient and responsive solutions for information services in educational institutions. By integrating the chatbot into the Telegram application, it is expected to facilitate users in quickly and accurately obtaining information. This chatbot is built with a Retrieval Augmented Generation (RAG) approach that enhances LLM capabilities and helps in obtaining fast and accurate information. The chatbot is developed using software such as Langchain to manage the RAG process, Python as the programming language, ChromaDB as the vector database, and Gemini AI to support the LLM model. Performance evaluation is conducted using RAGAS to ensure the quality and accuracy of responses. Testing with 10 sample questions showed positive results, a context precision score of 93%, faithfulness 100%, answer relevancy 96%, context recall 100%, answer correctness 71%, and answer similarity 93%. These results indicate that an RAG-based chatbot can be an effective tool to improve information accessibility in educational institutions.

Implementasi Pengamanan Terhadap Server Menggunakan Next Generation Firewall (NGFW)

Syahrul Ramadhan Nuriana — 2024-11-30

The high use of information technology carries a significant risk of cyber attacks, making it important for organisations to secure their servers to prevent intrusion and data leaks. This research focuses on the development and implementation of a CheckPoint Next Generation Firewall (NGFW) configured to mitigate cyber attacks, especially those included in the OWASP Top 10, with a Network Development Life Cycle (NDLC) approach. The research results show that implementing NGFW effectively improves server security and protects against cyber attacks. These findings emphasize the importance of NGFWs in an organization's network security architecture, with the right configuration serving as a proactive mitigation tool against cyber threats.

Analisis Profil Peserta Webinar Implementasi Kurikulum Merdeka dengan Microsoft Power BI untuk Meningkatkan Akses dan Kualitas Pembelajaran

Sri Kuswayati — 2024-11-30

Implementation of Kurikulum Merdeka faces a number of challenges. One of the main challenges is the readiness and competence of educators in understanding and implementing this new curriculum. Implementing webinars has become a popular solution for delivering information and training regarding the Kurikulum Merdeka, but its effectiveness still needs to be further evaluated to ensure that all educators can access and utilize this information well. Analysis of an in-depth understanding of the profile of webinar participants is important to design professional development programs that are more targeted and effective. This research uses Microsoft Power BI and a quantitative descriptive approach which aims to provide an overview of the characteristics of webinar participants based on numerical data collected through participation data. This research population includes all participants from webinar series 1, 2, 3, and 4 regarding the Implementation of the Independent Curriculum. Sampling used a purposive sampling technique, with samples taken from 182 participants who actively took part in the webinar series. The results show that the elementary school level is the type of institution that has the most registrations for the entire webinar series. However, it should be noted that the total number of participants at other levels in each series is relatively small, especially for levels other than elementary school. This may affect the validity of the generalization. This indicates the possibility of other factors influencing the number of registrants at each level. For further research, it is recommended to collect more complete data on participant characteristics, such as geographic location, field of study, and reasons for enrollment.

Peningkatan Visibilitas Produk pada Rekomendasi Long-Tail dengan Pendekatan Frequent Maximal Itemset

Rosyid Muarif — 2024-11-30

Long-tail products are often overlooked in Collaborative Filtering recommendation systems due to their low purchase frequency and reliance on user interaction history. This study proposes the use of a Frequent Maximal Itemset (FMI) to improve the visibility of long-tail products in an online electronic cigarette (vape) store. Unlike Collaborative Filtering, FMI does not require user data and identifies historical transaction patterns to recommend relevant long-tail products alongside popular ones. Experimental results show that FMI is effective in identifying maximal itemsets that combine popular and long-tail products. Validation with 10 users revealed that 90% found the recommendations relevant to the main products they were searching for, and 90% indicated that they were likely to try the recommended long-tail products. The long-tail products included in the recommendations had logical associations with popular products, such as nicotine liquids with vaping devices. Thus, the FMI approach proves to be more flexible and effective in addressing popularity bias, while also providing long-tail products with greater visibility and increasing their potential for sales.

Pengembangan Sensor IOT Untuk Monitoring Kualitas Udara di Area Perkantoran

Reza Bintang Suherman — 2024-11-30

Air pollution poses a significant threat to public health and the environment. To address this issue, the development of Internet of Things (IoT)-based air quality monitoring systems has gained prominence. This study aims to design and analyze an IoT-based system capable of real-time monitoring of various air quality parameters such as PM 2.5, CO, CO2, temperature, humidity, and air pressure. Through a literature review and conceptual system design, the study identifies the potential of IoT-based systems in improving air quality understanding and decision-making. However, challenges including sensor advancement, reliable connectivity, power infrastructure, and data security must be overcome. By addressing these challenges, IoT-based air quality monitoring systems can play a crucial role in maintaining healthy air quality for communities.

Mengoptimalkan Platform Pembelajaran Online untuk Meningkatkan Keterlibatan Siswa Selama Pandemi COVID-19

Muhamad Darlan — 2024-11-30

The COVID-19 pandemic has necessitated drastic changes in higher education, leading to a sudden shift to online learning. This literature review analyzes the effectiveness, influencing factors, challenges, and solutions in the context of online learning during the pandemic from 2020 to 2022. A systematic review methodology was employed, including searches in major databases, screening of 150 initial articles, and final analysis of 50 selected studies. The results show a positive effectiveness of online learning (d = 0.38), emphasizing the quality of teacher-student interaction, course design, technology competency, institutional support, and intrinsic motivation. Challenges like internet connectivity and social interaction were identified, with solutions including technology infrastructure, digital training, alternative assessment methods, and psychosocial support. Further research is recommended for longitudinal studies and specific strategies to enhance student engagement in online learning.

Optimalisasi Jaringan Internet Sekolah dengan Fiber Optic, UTP Cat 6, dan VLAN

Budi Sunaryo — 2024-11-30

The use of the internet in schools has become essential to support teaching and learning activities, but issues such as uneven network distribution and suboptimal performance often arise. This study aims to address these problems by implementing Fiber Optic, UTP Cat 6, and Virtual Local Area Network (VLAN) technologies to enhance the stability and speed of the school’s internet network. Using the Network Development Life Cycle (NDLC) method, which includes analysis, design, simulation, implementation, and monitoring phases, the study results showed a 30% increase in network throughput and a reduction in average latency by 15%. Additionally, the VLAN configuration successfully separated data traffic, improving the security and efficiency of the network. The network was able to support more than 1000 users with stable performance. In conclusion, the implementation of these technologies significantly optimized the school’s internet network and can serve as a technical guide for other schools seeking to improve their network quality.

Analisis Kebutuhan Sistem Informasi untuk Smart Irrigation di Kabupaten Agam

Zulfadli Zulfadli — 2024-11-30

Agriculture plays an important role in the economic structure of Agam Regency, where the majority of the population relies on agriculture as their main source of income. A well-functioning irrigation system is essential to support this agricultural sector, and its optimal management is essential. Inadequate irrigation management can have various negative impacts, including the conversion of agricultural land into empty or unproductive land, which then impacts regional income and the welfare of local farmers. This study emphasizes how irrigation assets are managed in Agam Regency and the obstacles encountered. In a region that is predominantly dependent on agriculture, approximately 70% of the land is used for agriculture, including 885 irrigation sites that require efficient management and rehabilitation, often carried out by authorities together with farmer groups. This research focuses on answering the urgent need for an integrated information system for irrigation management in Agam Regency. It is aspiring to develop a roadmap for implementing smart irrigation through information systems. Furthermore, practical investigations will develop information systems to facilitate decision-making processes in better irrigation management. The research methodology uses a qualitative descriptive method, which involves collecting data through questionnaires and interviews with relevant stakeholders, parties from government and farmer groups. Data will be processed using descriptive statistical analysis, focusing on the main problems identified during the research. Result of this study as a basic step towards developing an integrated information system for smart irrigation management in Agam Regency, which aims to improve agricultural sustainability, increase income and resource efficiency.

Kajian Kerentanan Keamanan Website Universitas XYZ Menggunakan Framework Open Web Application Security Project (OWAS)

Teguh Reskya Ramadhan — 2024-11-30

Website security is a critical priority for educational institutions, including XYZ University, to safeguard their data and services from cyber threats. This study aims to assess the security vulnerabilities of XYZ University's website using the Open Web Application Security Project (OWASP) framework. The analysis revealed that the website has high-security risks with multiple vulnerabilities, such as Injection, Cross-Site Scripting (XSS), and Security Misconfiguration. The study employs an OWASP-based approach, encompassing risk identification, vulnerability analysis, and mitigation recommendations. The findings indicate that the primary weaknesses stem from inadequate input data protection, delayed software updates, and weak access controls. This research provides strategic recommendations to mitigate security risks, including strengthening input validation, updating systems, and implementing robust data encryption mechanisms. The results are expected to enhance the security posture of XYZ University's website and serve as a reference for proactive measures against cyber threats.

Sistem Keamanan IoT dengan Sensor RFID dan Kamera ESP32 untuk Verifikasi Identintas dan Visual

Imam Gunawan — 2024-11-30

The main problem faced by the madrasah is the lack of visual evidence that can cause a number of problems, including misuse of access cards and the inability to identify perpetrators using fake cards if they want to adopt RFID technology as a security system. This study aims to develop an Internet of Things (IoT)-based security system at Madrasah Ibtidaiyah Wathoniyah Sumber Makmur by utilizing RFID sensors and ESP32 cameras. The system developed is designed to automatically verify identity and provide visual notifications sent via Telegram. The research process began with the collection of qualitative data through direct observation and interviews with the principal, which provided in-depth insights into the existing problems, history, and vision, mission, and organizational structure of the madrasah. Library research was also conducted to collect information from various relevant books and scientific articles, providing the theoretical basis needed for system development. In addition, laboratory research focused on testing and validating prototypes involving hardware components such as ESP32, ESP32 Cam, and PN532 sensors as well as software developed using software such as Arduino IDE, Telegram, and Visual Studio Code. The development method in this study uses a prototyping method that involves active collaboration between designers and end users to ensure that the resulting solution is in accordance with user needs and expectations. The conclusion is that the developed system significantly improves security and access management in madrasahs. This system has proven effective in reducing the risk of access card misuse by providing the necessary visual evidence and accurately detecting illegal access attempts, and can identify perpetrators in illegal access attempts with fake access cards that can be spam.

Model Rekomendasi Makanan Menggunakan Content-Based dan Collaborative Filtering

Falahah Falahah — 2024-11-30

The Food Recommendation System is one of the most popular implementations of the recommendation system in everyday life.

Prototipe Sistem Deteksi Dini Banjir Menggunakan Maket Aliran Sungai dan Sensor Ketinggian Air Berbasis Internet of Things

Ery Muchyar Hasiri — 2024-11-30

Floods are a natural phenomenon that occurs when water from rivers, lakes, or seas exceeds its boundaries and inundates surrounding areas, posing threats to humans and animals and causing environmental and infrastructure damage. This study aims to develop an effective early flood detection tool for river areas utilizing IoT technology. The research methodology begins with identifying needs through problem formulation and a literature review on the latest flood detection technologies and the application of IoT in environmental monitoring systems. The designed system involves integrating sensors to monitor flood parameters such as water level and rainfall, with data transmitted in real-time to an IoT-based monitoring center. Development includes designing data analysis algorithms and developing hardware (resistive sensors, NodeMCU) and Android software. Implementation involves installing sensors at strategic locations and testing the system to validate the accuracy and performance of early warnings. System response evaluation is conducted through flood simulations and real conditions, with results disseminated to authorities and the public. Using river coastal models in the simulation system facilitates understanding of field conditions and serves as an educational tool to raise public awareness. On September 17-20, 2023, testing was conducted on the early flood detection simulation tool and the river flow model using the IoT system. Test results indicated that water levels at all locations had a minimum value of 0 cm and a maximum of 10.73 cm on September 18, 2023. Location 4 consistently showed the presence of flooding. This data integration provides a strong basis for authorities in flood disaster planning and management, enabling a faster and more effective response to detected conditions.

Sistem Pendukung Keputusan untuk Penentuan Klasifikasi Status Hotel

Billy Eden William Asrul — 2024-11-30

The Hotel industry is a key component of the tourism sector that is required to obtain business certification. This certification determines the star classification of a hotel. The determination of 1, 2, 3, 4, and 5-star classifications for hotels, particularly in the city of Makassar, involves the Tourism Business Certification Agency (LSUP) as the auditing body, the Makassar City Tourism Office as the regulatory body responsible for supervision and guidance, and the industry as the auditee. The conventional and manual processes for determining star ratings reduce the effectiveness and efficiency of audit implementation, as well as hinder the supervision of business certification by the Makassar City government.

Bibliometrik Analisis: Utilization of Machine Learning Technology in the Management of Healthcare Database System

Nana Suarna — 2024-11-30

Healthcare databases store various types of data, including patient records, medical imaging, and real-time monitoring data. Efficient data management is crucial for improving patient outcomes and operational efficiency. Traditional methods face limitations in terms of scalability, data heterogeneity, and real-time processing. The main challenge in healthcare database management is the ability to efficiently process and analyze large volumes of heterogeneous data. Existing systems struggle with scalability, data integration, and real-time analytics, leading to delays in decision-making and potential errors in patient care. Methodology this research uses machine learning algorithms to enhance the performance and capabilities of healthcare database systems. Techniques such as data mining, predictive analytics, and anomaly detection are applied to optimize data storage, retrieval, and analysis processes. A comparative analysis is conducted between traditional database management systems and ML-enhanced systems to evaluate improvements in efficiency, accuracy, and scalability. The main objective is to demonstrate how ML can be leveraged to overcome existing challenges in healthcare database management. This includes improving data processing speeds, enhancing data integration from various sources, and enabling real-time analytics for better clinical decision-making. Results the findings show that the integration of ML technology significantly enhances the performance of healthcare database systems. The ML-enhanced systems demonstrated improved scalability, faster data retrieval, and more accurate predictive analytics compared to traditional systems. These improvements facilitate timely and informed decision-making in clinical settings, ultimately leading to better patient outcomes.

Transformasi Sistem Informasi Akuntansi: Optimalisasi Efisiensi dengan AI dan Keamanan Siber

Binastya Anggara Sekti — 2024-11-30

Understanding the value of an effective and efficient Accounting Information System

Representasi Pengetahuan Sistem Pakar Menggunakan Struktur Data Redis

Haddad Sammir — 2024-11-30

This research discusses knowledge representation in expert systems using the Redis data structure, with a focus on the knowledge-based inference process. Inference in an expert system involves comparing existing facts with an existing database. When the elements in the rule match the database, the rule is considered TRUE and processed further in the database. For efficiency and speed in the inference process, this research utilizes the Redis data structure, especially the "sets" data structure type, which allows set operations to be carried out quickly and effectively. This research also suggests a convention for writing keys and values in Redis so that data consistency and integrity is maintained. Through this implementation, it is hoped that the expert system can process and make decisions more efficiently, utilizing Redis' advantages in set-based data management and access.