PENGGUNAAN METODE GLCM DENGAN DEEP LEARNING UNTUK PERBANDINGAN KLASIFIKASI BAHAN MAKANAN
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This study is a report on the results of using several methods to show the level of accuracy for six food items, with a sample size of 50 images for each food item. This study applied the GLCM and Deep Learning methods to perform classification. The results of testing and program development show that the DecisionTree Classifier has an accuracy of 0.32%, LogisticRegression 0.28%, Bagging Classifier 0.23%, GradientBoost Classifier 0.37%, InceptionV3 0.93%, ResNet50 0.30%, and Xception 0.85%. From the results obtained, it can be concluded that the Deep Learning method with the InceptionV3 model is the best choice because it successfully classified each food ingredient with the highest accuracy among the other models used.
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