Pengembangan Sistem Deteksi Penyakit Tanaman Tomat Melalui Citra Daun dengan Metode You Only Look Once (YOLO) Berbasis Android - Bagus Erwanto; Afu Ichsan Pradana; Dwi Hartanti (G-Tech: Jurnal Teknologi Terapan, 2024)
Agriculture plays a crucial role in Indonesia's economy, particularly in horticultural sub-sectors like fruit and vegetable production. Cultivation of tomatoes (Lycopersicum esculentum Mill) is one of the flagship commodities, but leaf disease attacks pose a major challenge that can reduce yields. Various studies have highlighted the need for computer vision-based plant disease detection solutions for tomatoes. This research focuses on developing a leaf disease detection application for tomato images on Android using the You Only Look Once (YOLO) method. Model evaluation was conducted using a confusion matrix and metrics such as precision, recall, and mAP (mean Average Precision). The results demonstrate high accuracy in classifying various diseases on tomato leaves. The model showed good performance in classifying different types of tomato leaf diseases, achieving an mAP of 96.6% and recall of 92.2% across all disease classes. Black box testing of the application indicated strong detection capabilities. This application has been successfully developed and released as 'Plantify' on Apkpure.