Alexander Ibrahim
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Implementasi Algoritma Yolo untuk Deteksi Kebusukan pada Sayur Kembang Kol Alexander Ibrahim; I Wayan Supriana
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 1 (2024): JNATIA Vol. 3, No. 1, November 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2024.v03.i01.p19

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.