KLASIFIKASI CITRA DAGING SAPI DAN DAGING BABIBERDASARKAN CIRI WARNA DAN TEKSTUR

The lack of meat in the market make the prices of meat increase significantly. Many butchers use this situation to get more profit by mixing the meat. There are some butchers who intentionally mix the beef with pork. Beef and pork is more easily differentiated by color and texture because of it has slightly different characteristics, but not all of customer knows the differences about that. Therefore, researchers will conduct research based on color and texture. The first step, the researches is performed image acquisition followed by a pre-processing. The next step is performed RGB color feature extraction and feature extraction texture of the first order. The results of feature extraction is used to do the classification using the K-Nearest Neighbour (K-NN). In this researche tested the combination of feature extraction parameters of color and texture that aims to determine which combination of parameters that show the best classification results. Phase analysis was used to find the highest level of accuracy of the classification results that obtained. Based on test results, it can be concluded that the combination of feature extraction parameters that produce high accuracy in image classification of beef and pork is a combination of parameters mean green color and texture parameters of entropy with the level of accuracy is about 94 percent and the computation time is 0,827 second.