Classification Of Egg Quality Using The K-Nearest Neighbor Algorithm In Machine Learning - Marantika, Windy; Gultom, Putri Romian; Agustine, William; Sinuhaji, Tama Ulina br; Aisyah, Siti; Amalia, Amalia; Radhi, Muhammad (Jurnal Sistem Informasi dan Ilmu Komputer, 2024)
In addition to meat, fish, and milk, one of the staple foods consumed by the community is chicken eggs. Egg quality assessment is separated into two categories: exterior (egg shell) and interior (egg contents). However, the evaluation method used in this investigation is focused on evaluating the external quality of eggs. Pre-processing, feature extraction, classification, and evaluation are steps taken in the image processing method used to classify chicken eggs. Classification methods that can be used include the K-Means Clustering and K-Nearest Neighbor (KNN) methods and improved KNN. Based on the findings in the study, the KNN improvisation method can be used to classify chicken egg quality, with a test accuracy value of 91.67%.