Determining Feasibility Level of Beef Quality Based on Histogram and K-Means Clustering

Beef is one of the staple foods that are consumed by many people. The rise of beef with poor quality on the market and the lack of knowledge of consumers and the public in distinguishing the quality of meat that is decent and not suitable for consumption when seen in plain view. The Department of Agriculture and Food of the City of Yogyakarta, especially Animal Slaughterhouse (RPH), Giwangan Yogyakarta in determining the quality of beef, still uses laboratory tests which take a long time. This study proposes a system to identify the image of beef that is suitable for consumption based on the color features generated from the image histogram with Hue, Saturation, and Intensity (HSI) color models and the K-Means Clustering method. The results of identification carried out on 40 test data obtained maximum and minimum values of HSI from each feasibility category.