Detection of Diseases and Pests on The Leaves of Sweet Potato Plants sing Yolov4
DOI:
https://doi.org/10.36805/bit-cs.v5i1.6065Keywords:
Yolov4, Detection, Sweet Potato, PlantsAbstract
Sweet potato (Ipomea batats) is a root plant that can live in all weather, in mountainous areas and on the coast.. This plant is one of the important food crops in Indonesia, and makes Indonesia the second largest sweet potato producer after China. However, according to data from the Central Statistics Agency (BPS), sweet potato production in Indonesia in 2018 decreased by 5.63% when compared to production in 2017 which reached 1,914,244 tons (Gultom, 2021). Based on these data, it is important to conduct research on pest and disease detection in plants. Therefore, the author conducted a study related to this problem entitled Detection of Diseases and Pests on the Leaves of Sweet Potato Plants using Yolov4 with the aim of helping educate farmers in recognizing diseases on the leaves of sweet potato plants and how to overcome them. In this study the dataset was sweet potato leaves with a total of 1500 data divided into three classes, namely aspidomorpha, yellow spot and normal leaves with 4000 iterations. The best training results on 1500 data with 75% accuracy. The Yolov4 algorithm produces high accuracy in detecting diseases in the leaves of sweet potato plants.
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