Klasifikasi Kesegaran Daging Sapi Menggunakan Metode Ekstraksi Tekstur GLCM dan KNN - Ade Prabowo; Danang Erwanto; Putri Nur Rahayu (LPPM Poltek ST Paul, 2021)
Meat is the soft part of the animal that is covered by skin and is attached to the bones which become food ingredients. This research was conducted to classify the types of fresh, inn and rotten beef using 120 samples of beef taken directly by the researcher. Before classifying the type of beef, the texture of the beef image was extracted using the GLCM method to produce texture parameters in the form of contrast, correlation, homogeneity and energy. Texture parameters are classified using the KNN method. The results in this study indicate that the extraction of beef image texture using the GLCM method can produce various values on the 4 parameters of the GLCM texture. In addition, the results of the classification of beef freshness using the KNN method to determine 3 types of meat quality, namely fresh, cooked and rotten beef, obtained an evaluation of the classification performance using the Confusion Matrix table with an Accuracy value of 0.82, Precision of 0.83, Recall of 0.82 and F-Measure of 0.82. So that the parameters of the beef image texture using the GLCM method can be classified properly using the KNN method.