Rancang Bangun Sistem Klasifikasi Rasa Permen Karet Berdasarkan Warna Dengan Metode K-Nearest Neighbor (KNN) - Wisnu Mahendra; Dahnial Syauqy; Agung Setia Budi (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2020)
Gum candy is a pretty much food forth by the Indonesian society because rawish gum can increase concentration and can also remove stress. Many types of taste contained in gum is and every person have a kind of favorite taste in different gum. In one container of rubber candy that has been issued by the factory or which is contained in the store has been mixed with various sense of gum. And make people hard to choose the type of sense of rubber gum according to the preferred. Therefore, the design prototype of the taste classification process in gum candy using K-Nearest Neighbor method. In this study using TCS3200 color sensor connected with arduino nano microcontroller. This sensor will later read every color on gum. The method used in this study is K-Narest Neighbor for calculation of classification on gum. From the test results that have been made there is a percentage of error of the TCS3200 color sensor reading of 0.23%. The result of testing on the casification of the rawish casification class by using the K-Narest Neighbor method with 10 times tested obtained 90% accuracy and average computing time of 3.1494 seconds.