G-Tech : Jurnal Teknologi Terapan
Vol 8 No 3 (2024): G-Tech, Vol. 8 No. 3 Juli 2024

Pengembangan Sistem Deteksi Penyakit Tanaman Tomat Melalui Citra Daun dengan Metode You Only Look Once (YOLO) Berbasis Android

Bagus Erwanto (Universitas Duta Bangsa Surakarta, Indonesia)
Afu Ichsan Pradana (Universitas Duta Bangsa Surakarta, Indonesia)
Dwi Hartanti (Universitas Duta Bangsa Surakarta, Indonesia)



Article Info

Publish Date
02 Jul 2024

Abstract

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.

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Journal Info

Abbrev

g-tech

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

Description

Jurnal G-Tech bertujuan untuk mempublikasikan hasil penelitian asli dan review hasil penelitian tentang teknologi dan terapan pada ruang lingkup keteknikan meliputi teknik mesin, teknik elektro, teknik informatika, sistem informasi, agroteknologi, ...