classification of amaranth leaf disease using the support vector machine (svm) method

Abstract

The classification of leaf diseases in amaranth plants provides a promising step towards
sustainable food security in agriculture. Production Costs can also be significantly increased if
plant diseases are not detected and cured in the early stages. Support Vector Machine (SVM) is
an algorithm that can classify the types of diseases in spinach leaves. The image was taken
using a smartphone as many as 1426 images divided into 3 classes. The class in this study
represented 2 types of diseases in spinach leaf plants, namely hollow disease, and rust disease.
This study proposes a classification of diseases in the leaves of amaranth plants based on the
texture features of the Grey Level Co-occurrence Matrix. then carried out the classification of
amaranth leaf disease using the support vector machine (svm) method. The results of the
experiment successfully classified between hollow spinach leaf disease and rust spinach leaf
disease using the Support Vector Machine (SVM), the correct recognition rate of the training
data was 54.6293 percent, and the correct recognition rate of the image test was 57.2614
percent.

Keywords— Keywords: Spinach Leaf Disease Classification, Support Vector Machine (SVM),
Grey Level Co-occurrence Matrix (GLCM).