Implementasi Algoritma Yolo untuk Deteksi Kebusukan pada Sayur Kembang Kol

  • Alexander Ibrahim Universitas Udayana
  • I Wayan Supriana Universitas Udayana

Abstract

This research utilizes the YOLOv8 algorithm to detect spoilage in cauliflower vegetables. Image data was collected from Google, processed using Roboflow, and tested using Google Colab. The study results indicate an accuracy of 59%, recall of 58%, and MAP of 60%. The YOLOv8 algorithm significantly contributes to image recognition and visual data processing. Additionally, the article discusses the application of the YOLOv8 algorithm for object detection in 360-degree panoramic images. The training process was conducted to recognize objects in the images, and evaluation was performed using a confusion matrix and mAP50. The evaluation results demonstrate the model's good performance in object recognition. Several references cited in the article are also included.


Keywords: You Only Look Once (YOLO), Google Colab, Roboflow

Published
2024-11-01
How to Cite
IBRAHIM, Alexander; SUPRIANA, I Wayan. Implementasi Algoritma Yolo untuk Deteksi Kebusukan pada Sayur Kembang Kol. Jurnal Nasional Teknologi Informasi dan Aplikasnya, [S.l.], v. 3, n. 1, p. 1047-1054, nov. 2024. ISSN 3032-1948. Available at: <https://ojs.unud.ac.id/index.php/jnatia/article/view/116022>. Date accessed: 08 jan. 2025. doi: https://doi.org/10.24843/JNATIA.2024.v03.i01.p19.