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Rendi Azrian
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Computer Science & IT Electrical & Electronics Engineering

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Identification of Barangan Banana Ripeness Treatment Types using k-Nearest Neighbor Abdullah Abdullah; Rendi Azrian
Sistemasi: Jurnal Sistem Informasi Vol 11, No 3 (2022): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v11i3.2281

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%.
Co-Authors Abdullah Abdullah