EKSTRAKSI CIRI BIBIT KACANG HIJAU MENGGUNAKAN METODE K-NEAREST NEIGHBOR

Abstract

Mung bean (Vigna Radiata) is a type of palawija which is widely known in the tropics. This plant belonging to the legume tribe (Fabaceae) has many benefits in everyday life as a source of high protein vegetable food. Mung bean in Indonesia ranks third most important as a legume food crop, after soybeans and peanuts. The most valuable part of the economy is the seeds. Although mung bean is a fairly popular plant, people who cultivate mung bean still often make mistakes when choosing seeds, resulting in less than optimal growth of mung bean to premature death of beans that grow on improper seeds, this can be overcome using a system digital image to determine whether the seed is viable or not. In this study, the data object is an image that will be processed using a color moment to get the image results in the form of numbers (histograms). Color features are the basis of an image because they have a strong relationship with an object. One method of recognizing color features by performing extraction is color moment. Color Moment is a solid representation of color features in characterizing image colors. These results become input for processing using KNN. The K-Nearest Neighbor (KNN) algorithm is a method for classifying objects based on the learning data that is closest to the object.