K-Nearest Neighbor Untuk Klasifikasi Jenis Buah Berdasarkan Berat, Tinggi, dan Lebar
Muhammad Rizq Naufal Mutawakkil Muhammad Fizkry Yusuf AL Fadillah · Zenodo (CERN European Organization for Nuclear Research) · 2023
Determination of the type of fruit can use several indicators. Indicator that can be used are the weight, height and width. In this research, method to determine and classify fruit using K-Nearest Neighbor method (kNN). The total data used for this research is 59 data. There There are 3 indications to determine the type of fruit, namely weight, height, and wide. The test scenario that was carried out was to divide the data into 80% for training data and 20% for test data with neighboring parameter values (k). The value of "k" tested was 5 and obtained an accuracy of 99.4%. The results obtained are able to classify types of fruit based on weight, height and width as well as the KNN algorithm which determines the type of fruit.