IMPLEMENTATION OF YOU ONLY LOOK ONCE V8 ALGORITHM IN POTATO LEAF DISEASE DETECTION SYSTEM

Bagus kurniawan Ekhsanto; Bagus Adhi Kusuma; Adam Prayogo Kuncoro

doi:10.52436/1.jutif.2024.5.4.2104

Bagus kurniawan Ekhsanto Informatics, Computer Science Faculty, Universitas Amikom Purwokerto, Indonesia
Bagus Adhi Kusuma Informatics, Computer Science Faculty, Universitas Amikom Purwokerto, Indonesia
Adam Prayogo Kuncoro Informatics, Computer Science Faculty, Universitas Amikom Purwokerto, Indonesia

DOI: https://doi.org/10.52436/1.jutif.2024.5.4.2104

Keywords: agriculture, detection system, potato leaf diseases, YOLOv8

Abstract

Agriculture is an important foundation of the national economy, as effective development in this sector will support overall economic stability. Potato itself is one of the world's staple foods after rice, wheat and corn. This crop belongs to the category of horticulture which is widely planted and developed by people to meet their needs. On the farm of Bibit sida kangen Kalibening, Banjarnegara which is one of the farms that grow potatoes has constraints related to potato diseases which result in decreased productivity of crops. Therefore, the main purpose of this system is to provide fast and accurate disease detection capability on the farm of Bibit sida kangen Kalibening, Banjarnegara, so that it can help farmers in reducing losses caused by disease attacks on plants. By utilizing YOU ONLY LOOK ONCE V8 (YOLOv8) technology, this system can recognize and classify potato leaf disease types, including early_blight, late_blight, and healthy plants, with a high level of accuracy. Through evaluation using precision and recall matrices, the results show a significant success rate, with precision accuracy for early_blight of 87%, healthy plants of 81%, and late_blight of 97%, respectively. Meanwhile, the recall results for the three categories also reached 87%, 81%, and 97% respectively. With an overall accuracy of 88%, these findings confirm that the developed detection system is successful in identifying potato leaf diseases with high accuracy. This indicates the great potential of this system in assisting farmers in managing the condition of their potato crops, which in turn can improve farmers' productivity and welfare.

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