Track: Modeling and Simulation

Abstract

The freshness of beef becomes the most important factor affecting the quality of the meat. The need for beef continues to increase, indicating that awareness of the importance of eating meat is getting higher and higher. With the high
price of beef in the market, it makes some people who cheat mix the quality of beef with cut meat that has been stored for a long time. The purchase of beef is usually carried out to identify the freshness of the meat with the naked eye
and sense of smell as well as direct contact by suppressing the texture of the meat. However, this method has the disadvantage that consumers are not observant and have difficulty distinguishing the quality of beef freshness.
Therefore, in this study, we tried to examine the level of freshness of beef by using the TGS 2602, MQ - 135 gas sensors as detectors of voc and ammonia compounds produced by meat and the TCS3200 color sensor by using RGB
values as identification of the beef. This study also analyzed the level of beef freshness with indicators obtained from the three sensors using the K- Nearest Neighbor method. In this study, there were 3 conditions of the level of freshness of the meat tested, namely fresh meat, slightly fresh meat, and non-fresh meat with an accuracy rate of 93%.