PENENTUAN LEVEL KEMATANGAN KOPI BEDASARKAN HASIL ROASTING MENGGUNAKAN METODE DETEKSI RGB DAN KLASIFIKASI MINIMUM DISTANCE - Ade Febri Syah Putra (2020)
One of state revenue source through non-oil and gas exports is plantation products, in which coffee has a significant contribution to the increase of non-oil and gas exports in Indonesia. One of the stages that are very important to influence the taste of coffee is the roasting process. The results of grilling are defining into three classes, namely light roast, medium roast, and dark roast. Currently the classification process is mostly done by conventional or manual methods which are means experts need to improve the baking process to classify the results of the roasting. Therefore, we need a system that can classify the roasted coffee beans as quick and accurate. In this case the researcher will make a Coffee Maturity Level Determination Application based on the results of roasting using the RGB detection method and minimum distance classification. This application uses nine indicators to determine the classification by RGB mean, RGB standard deviation, and RGB image variants. In the training and test data distribution using k-fold cross validation with the number k = 5, the average accuracy obtained was 89.63%.