Penerapan Metode Decision Tree dan Analisis GLCM dalam Mengidentifikasi Kualitas Buah Terung Berbasis Android

Abstract

Eggplant has become one of the preferred choices as a complementary ingredient in cooking for the community. The classification of the quality of eggplants is a crucial step for modern consumers who are increasingly aware of the importance of health. This awareness stimulates the desire to better understand the quality of the products consumed, especially in the case of vegetables. Classification can be a critical tool to ensure that consumers can make intelligent and healthy choices, distinguishing fresh fruit with optimal nutritional value from varieties that may have lost their freshness or become infected with diseases such as anthracnose. Based on this issue, the author applies a Gray Level Co-Occurrence Matrix analysis model, which is then compared using a Decision Tree algorithm based on Android to detect and classify fruit quality based on predetermined classes or labels. Using a total of 352 images, divided into 282 images for training and 70 images for testing, a success rate of 97.18% was achieved.