📅 28 January 2025
DOI: 10.62951/modem.v3i1.363
Sistem Deteksi Kualitas Cabai Rawit Menggunakan Metode YOLO: You Only Look Once
Modem : Jurnal Informatika dan Sains Teknologi
Asosiasi Riset Teknik Elektro dan Informatika Indonesia (ARTEII)
📄 Abstract
This research focuses on developing a cayenne pepper quality detection system using the YOLO (You Only Look Once) V5 algorithm. The system is designed to address the limitations of manual post-harvest sorting by classifying cayenne peppers into three categories: “good” (ripe), “bad” (rotten or dry), and “raw” (green), based on their visual characteristics. A dataset consisting of 565 images was manually collected, labeled using Roboflow, and pre-processed through resizing and orientation standardization. Model training was conducted over 150 epochs, achieving high detection performance with a mean average precision (mAP) of 99.5%, precision of 99.6%, and recall of 99.9%. Real-time testing demonstrated the system’s capability to detect and classify cayenne peppers with exceptional accuracy. This research is expected to enhance the efficiency and accuracy of the cayenne pepper sorting process, while paving the way for the application of YOLO-based systems to other agricultural commodities. Further research is recommended to expand the dataset and optimize model parameters for improved system performance.
🔖 Keywords
#YOLO algorithm; cayenne pepper quality detection; cayenne pepper classification; postharvest sorting system
ℹ️ Informasi Publikasi
Tanggal Publikasi
28 January 2025
Volume / Nomor / Tahun
Volume 3, Nomor 1, Tahun 2025
📝 HOW TO CITE
Azzam Ash'shobir, Abdulloh Haidar; Putri Harli, Kennyo Gendis; Putri Rudi, Adisty Pramudita; Syah Putro, Ilham Gusti; Putra Cahyono, Octavian Dava, "Sistem Deteksi Kualitas Cabai Rawit Menggunakan Metode YOLO: You Only Look Once," Modem : Jurnal Informatika dan Sains Teknologi, vol. 3, no. 1, Jan. 2025.
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