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Journal : KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika

Implementasi Metode K-Nearest Neighbors (KNN) Guna Mengetahui Klasifikasi Kematangan Stroberi Agus Widodo; Fitra Dwi Prasetya; Hendro Nugroho
KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Vol 3, No 2 (2022)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.kernel.2022.v3i2.4185

Abstract

To determine the maturity of the Strawberry fruit can be seen in the color of the fruit. The color of ripe strawberries can be seen in red and those that are not yet ripe are green. To determine the ripeness of strawberries, classification can be carried out on the fruit using feature extraction of the waena. The feature extraction results are classified using the K-Nearest Neighbors (KNN) method. The first method of classification of strawberry ripeness is (1) feature extraction using the Hue Saturation and Value (HSV) method, and (2) KNN. From the implementation results, the success rate of classification using the KNN method is 76%