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Klasifikasi Penyakit Daun Bayam Dengan Menggunakan Metode Support Vector Machine (SVM) Nunung parawati
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 14 No 2-b (2022): Jupiter Edisi Oktober 2022
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281./5048/5.jupiter.2022.10

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 57.2614percent. Keywords— Keywords: Spinach Leaf Disease Classification, Support Vector Machine (SVM), Grey Level Co-occurrence Matrix (GLCM).
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