Classification of Chili Leaf Disease Using the Gray Level Co-occurrence Matrix (GLCM) and the Support Vector Machine (SVM) Methods
Yuslena Sari, Andreyan Rizky Baskara, Rika Wahyuni
Abstract
Chili is a type of vegetable that has a very high economic value. The problem that often occurs in chili plants is that many agricultural losses are caused by disease. Plant diseases are always considered a very serious problem in all countries because economic growth is largely dependent on the agricultural sector in developing countries. In some plant, diseases sometimes caused by bacteria, viruses and fungi. To anticipate this problem, a method designed into a classification system for diagnosing chili leaf disease by applying the Gray Level Cooccurrence Matrix (GLCM) feature extraction method. Then classified using the Support Vector Machine (SVM) method. The output classification of disease diagnoses in chili obtained an overall accuracy level of 88%. The results obtained prove that the method of extracting the features of Gray Level Co-occurrence Matrix (GLCM) and Support Vector Machine (SVM) can be applied to diagnosing chili plants disease.