K-NN Klasifikasi Kematangan Buah Mangga Manalagi Menggunakan L*A*B dan Fitur Statistik - Arif Patriot Sri Pamungkas; Nur Nafi’iyah; Nur Qomariyah Nawafilah (Jurnal Ilmu Komputer dan Desain Komunikasi Visual, 2019)
Fruits are a food source of vitamins. The fruit is quickly damaged by mechanical, chemical and microbiological influences, making it easy to rot. Classification is carried out on a group of mangoes which differ in type of maturity. The distinguishing feature was used is the L*A*B color feature. The purpose of this researchgave the output of the maturity classification ofManalagi mangoes based on color features using the Matlab application. In this research the GLCM method will be proposed for feature extraction in mangoes. By using K-Nearest Neighboor (KNN) to determine the maturity level of the Mango fruit. The dataset used is 130 data, consisting of 65 data for raw, 15 for half-cooked and 50 for mature. The KNN Classification results using the GLCM and L*A*B methods for Feature Extraction get an accuracy value of 62.5% in the test data. Keywords— Matlab, Manalagi Mango, KNN, Lab, GLCM.