Klasifikasi Jenis Daging Sapi Dan Kuda Menggunakan Metode Support Vector Machine (SVM)

Abstract

Meat plays an important role in daily nutrition due to its high protein content, which helps support human intelligence and stamina. However, the similarities in color and texture among different types of meat often make it challenging to distinguish between them. This issue can be exploited by dishonest meat vendors who mix or substitute meat types, leading to potential health risks. Meat types can be differentiated by observing their fiber structure and color. This study aims to address the problem by focusing on the differences in meat color and texture, which can be identified through digital image processing. One effective approach proposed is using the support vector machine (SVM) method along with HSV feature extraction to distinguish between beef and horse meat. The study shows that using SVM and HSV feature extraction to classify beef and horse meat yields an accuracy of 93.3%, demonstrating the potential of this technology in accurately identifying meat types.