Identification of Barangan Banana Ripeness Treatment Types using k-Nearest Neighbor

Abstract

Bananas are favored by the public because bananas are rich in nutrients that our bodies need. One of the bananas that people are interested in is the Barangan. Bananas sold in the market have various types of ripeness that vary based on their treatment. This study aimed to identify the type of treatment for Barangan. Identification is carried out based on an analysis of the image of Barangan using color and texture features. The k-Nearest Neighbor (k-NN) method is used in the identification. The k-NN compares the similarity between the unknown data and the sample data. The k values used in this study are k=1, k=3, and k=5. The Euclidean Distance is used to measure the distance between 2 feature vectors. The classification test uses the holdout method, where the percentage of the amount of sample data and test data is 66.67% of training data and 33.33% of test data. The accuracy obtained at k=1 is 86.67%, at k=3 is 76.67%, and at k=5 is 80%. The best accuracy for identifying banana ripeness treatment types using the k-Nearest Neighbor method is obtained at k = 1, with accuracy reaching 86.67%.