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

Authors

  • Oddy Virgantara Putra Universitas Darussalam Gontor Ponorogo
  • Dihin Muriyatmoko Universitas Darussalam Gontor Ponorogo
  • Harris Abdillah Faqih Universitas Darussalam Gontor Ponorogo

Keywords:

stock monitoring, collaborative filtering, e-commerce, recommendation system, machine learning

Abstract

  1. 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.

References

Fernandez, M., Mulyawan, B., & Dolok Lauro, M. (2023). E-Commerce Website Application With Customer Loyalty and Recommendations Items Depends on Price Features Using K- Means Clustering Method. International Journal of Application on Sciences, Technology and Engineering, vol. 1, no. 2, pp. 457-472, 2023.

Firmansyah, M. D., & Herman, H. (2023). Perancangan Web E- Commerce Berbasis Website pada Toko Ida Shoes. Journal of Information System and Technology, vol. 4, no. 1, pp. 361-372, 2023.

Herny Februariyanti, Aryo Dwi Laksono, Jati Sasongko Wibowo, M. S. U. (2021). Implementasi Metode Collaborative Filtering Untuk Sistem Rekomendasi Penjualan Pada Toko Mebel. Jurnal Khatulistiwa Informatika, vol. IX, no. I, pp. 43-50, 2021.

Huang, G. (2022). E-Commerce Intelligent Recommendation System Based on Deep Learning. 2022 IEEE Asia-Pacific Conference on Image Processing, Electronics andComputers, IPEC 2022, pp. 1154-1157.

Li, L. (2024). Research on Personalized Recommendation System for E-Commerce Products Based on Collaborative Filtering Algorithm. 2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA), 2024, pp. 876-880.

Mishra, S. N., & Kumar, S. (2023). A Product based Recommendation System for E-Commerce Sites. Proceedings of International Conference on Computational Intelligence and Sustainable Engineering Solution, (CISES 2023), 2023, pp. 1005-1009.

Downloads

Published

2024-10-24

How to Cite

Oddy Virgantara Putra, Dihin Muriyatmoko, & Harris Abdillah Faqih. (2024). Pengembangan website Monitoring Stok Barang Supplier dengan Sistem Rekomendasi menggunakan metode Collaborative Filtering pada Ud. Pekanbaru Jaya. Prosiding SISFOTEK, 8(1), 213 - 217. Retrieved from http://seminar.iaii.or.id/index.php/SISFOTEK/article/view/489

Issue

Section

Sistem Informasi dan Teknologi