Klasifikasi Buah Jeruk Segar dan Busuk Berdasarkan RGB dan HSV Menggunakan Metode KNN - Napitu, Stifani; Paramita Panjaitan, Rini; Nulhakim, Putri Aisyah; Khalik Lubis, Muaz (Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen, 2023)
Fruits are a group of agricultural commodities in Indonesia. The demand for domestic fruit commodities is quite high, this is indicated by the large number of fruits available in modern markets and traditional markets. In this research, a classification process will be carried out between fresh oranges and rotten oranges based on RGB (Red, Green, Blue) and HSV (Hue, Saturation, Value) color extraction. This study uses the K-Nearest Neighbor classification algorithm with a value of k = 1; 2; 3; 4; 5; 6; and 7. The dataset used consists of 146 training data and 88 testing data. The purpose and benefits of this research are to save time and facilitate classification according to the wishes of fruit growers. The final result of the test accuracy is 88.95%. Based on the test, this system can be said to be quite good at classifying fresh and rotten citrus fruits.