Klasifikasi Tingkat Kematangan Susu Kefir dengan Metode K-Nearest Neighbor (KNN) menggunakan Sensor Cahaya dan Sensor Warna - Faizal Ardiansyah; Dahnial Syauqy; Gembong Edhi Setyawan (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Milk is a product that is classified as rare in Indonesian society and also the age of milk that is classified as short, making it difficult for the community to consume milk every day. Therefore, the prototype of the kefir milk fermentation process is designed using the K-nearest neighbor method. Starting from fresh cow's milk mixed with kefir seeds, after that the freshly mixed kefir milk will be inserted into the dark box in the box, there are color sensors and light sensors that are used to monitor color changes and the light intensity that occurs when fermentation is in progress. The readings obtained by the next two sensors will be determined using the K-nearest neighbor method. The test results obtained to determine the accuracy of the reading of the light sensor is worth 5.12% while the color sensor is worth 8.64% from the results of testing the two sensors, it can be concluded that the readings of the two sensors can be said to be quite good. The test results on the Kefir milk maturity level classification system using the K-nearest neighbor method with 10 times testing found an accuracy rate of 80%. And the average value of system computing time obtained after the calculation of the value of K obtained 353.3ms in 10 times the test.