K-Nearest Neighbor Untuk Klasifikasi Jenis Buah Berdasarkan Berat, Tinggi, dan Lebar

Muhammad Fizkry Yusuf Al-Fadillah
Muhammad Rizq Naufal Mutawakkil

Jurnal Ilmiah Wahana Pendidikan
Vol 9 No 10 (2023): Jurnal Ilmiah Wahana Pendidikan

Determination of the type of fruit can use several indicators. Indicators that can be used are weight, height and width. In this study, the method for determining and classifying the fruit using the K-Nearest Neighbor (kNN) method. Total data used for this research there are 59 data. There are 3 indications to determine the type of fruit, namely weight, height, and width. Scenario The test carried out is to divide the data into 80% for training data and 20% for test data with neighbor parameter value (k). The "k" value tested was 5 and got an accuracy of 99.4%. Results that obtained is that we can classify fruit types based on weight, height and width and kNN algorithm that determines the type of fruit.