Prediksi Status Gizi Balita Dengan Algoritma K-Nearest Neighbor (KNN) di Puskemas Cakranegara

Abstract

Nutritional status is a picture of a person's physical condition as a reflection of the balance of incoming and outgoing energy by the body. Determining the nutritional status of toddlers is useful for knowing the nutritional status of toddlers based on weight/age (weight for age). The system designed is a system for determining the nutritional status of toddlers using the K-Nearest Neighbor (KNN) method, where the KNN method is a method of classifying or grouping test data whose class is unknown to the nearest neighbors using the distance calculation formula. The variables used in this system are based on anthropometric data or measurements of the human body, namely gender, age and weight. This system is designed and built using the PHP programming language and MySQL database. The results of this system are nutritional status based on body weight for age (weight for age), namely malnutrition, undernutrition, good nutrition, over nutrition. Based on the test results, the accuracy of the success rate for determining the nutritional status of toddlers using the KNN method produced by this system reaches 88.06%.