Metode Algoritma Convolutional Neural Network pada Klasifikasi Penyakit Tanaman Cabai

Abstract

In Indonesia, chili is a very important vegetable, which is consumed for domestic trade as well as for export. In addition to containing nutrients, chili also has a high economic value. Due to the increasing quality of chili as a commodity that often experiences the highest price fluctuations, it is necessary to classify chili plants to maintain the quality of chili harvests so that chili production can increase. This research is a classification of chili plant diseases using the convolutional neural network method, with several design and implementation processes. The purpose of this research is to assist in classifying the quality of chili plants in the hope of maintaining the quality of chili in the market and preventing the price spikes. Classification of chili plant diseases using a convolutional neural network based on train data and test data. To form a model in the classification, training data needs to be carried out and there are 3 categories used for the classification model, namely yellowish, leaf curl, and healthy. Training data compatible with computers in single GPU mode and validation data are not included in the training process as well as interpreter review materials to determine the type of chili plant object that is difficult to distinguish significantly, namely the results of the classification label that appears on the network.