Klasifikasi Daun Kelor Kering Berbasis Vision Artificial Intelegence

Authors

  • I Wayan Sudiarsa Institut Bisnis dan Teknologi Indonesia
  • Gede Agus Santiago Institut Bisnis dan Teknologi Indonesia

Keywords:

kelor, artificial, intelligence, IoT, vision

Abstract

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.

References

Riskianto, S. E. Kamal, and M. Aris, “Aktivitas Antioksidan Ekstrak Etanol 70% Daun Kelor ( Moringa oleifera Lam.) terhadap DPPH,” J. Pro-Life, vol. 8, no. 2, pp. 168–177, 2021.

D. A. Kusmardika, “Journal Of Health Science and Physiotherapy,” Potensi Akt. Antioksidan Daun Kelor (Moringa Oleifera) dalam Kangker, vol. 5, no. 3, pp. 248–253, 2020.

M. Warnis, L. A. Aprilina, and L. Maryanti, “Pengaruh Suhu Pengeringan Simplisia Terhadap Kadar Flavonoid Total Ekstrak Daun Kelor (Moringa oleifera L.),” Semin. Nas. Kahuripan, pp. 264–268, 2020.

I. Kurniawati and M. Fitriyya, “Characteristics of Moringa Leaf Flour with Sunlight Drying Method,” J. Gizi dan Pangan, vol. 1, pp. 238–243, 2018.

L. S. Marhaeni, “Daun Kelor (Moringa oleifera) Sebagai Sumber Pangan Fungsional dan Antioksidan,” Agrisia, vol. 13, no. 2, pp. 40–53, 2021.

J. Dian, F. D. Silalahi, and N. D. Setiawan, “Sistem Monitoring Detak Jantung Untuk Mendeteksi Tingkat Kesehatan Jantung Berbasis Internet Of Things Menggunakan Android,” JUPITER (Jurnal Penelit. Ilmu dan Teknol. Komputer), vol. 13, no. 2, pp. 69–75, 2021.

P. Sugiartawan, R. Pulungan, and A. K. Sari, “Prediction by a Hybrid of Wavelet Transform and Long-Short-Term-Memory Neural Network,” Int. J. Adv. Comput. Sci. Appl., vol. 8, no. 2, pp. 326–332, 2017.

P. Sugiartawan, S. Hartati, and A. Musdholifah, “Modeling of a Tourism Group Decision Support System using Risk Analysis based Knowledge BaseNo Title,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 7, pp. 354–363, 2020.

I. wayan Sudiarsa, P. Sugiartawan, I. G. I. Sudipa, N. M. Maharianingsih, and I. K. A. Putra, “Sistem Pengering Daun Kelor Berbasis Internet of Things dan Artificial Intteligence,” IJEIS (Indonesian J. Electron. Instrum. Syst., vol. 13, no. 2, p. 183, 2023, doi: 10.22146/ijeis.89823.

A. Taufan et al., “Studi Eksperimental dan Model Matematika Pengeringan Daun Kelor (Moringa Oleifera) dengan Empat Tipe Pengeringan,” J. Ris. Teknol. Ind., vol. 14, no. 2, p. 341, 2020, doi: 10.26578/jrti.v14i2.6518.

Downloads

Published

2024-10-26

How to Cite

I Wayan Sudiarsa, & Gede Agus Santiago. (2024). Klasifikasi Daun Kelor Kering Berbasis Vision Artificial Intelegence. Prosiding SISFOTEK, 8(1), 351 - 356. Retrieved from https://seminar.iaii.or.id/index.php/SISFOTEK/article/view/514

Issue

Section

Sistem Informasi dan Teknologi

Similar Articles

You may also start an advanced similarity search for this article.

bk8