Image Classification of Meat Using Support Vector Machine Method - Yuli Christyono; Sukiswo (PT. Banjarese Pacific Indonesia, 2024)
Meat is one of the essential food ingredients in meeting the nutritional needs. The current problem lies in the consumers' lack of knowledge on how to differentiate between pork, beef, goat, and lamb meat. This is because when the meat is already cut, their appearances may seem similar at first glance. Many consumers are unaware of the practice of mixing different types of meat for consumption. One way to classify animal meat is by using image processing. In this research, an image processing system is created to classify meat, specifically pork, beef, goat, and lamb. Support Vector Machine (SVM) is a development of Machine Learning that can be used in classifying images into specific classes. SVM method as a classifier is performed using a confusion matrix. The test results show the highest accuracy value obtained in the class of Goat Meat 91.4%, the highest precision in the class of goat meat 80%, the highest recall in the class of beef 81.3%, and the highest F1-score in the class of beef 0.76.