Klasifikasi Status Gizi Bayi Menggunakan Algoritma K-NN Pada Puskesmas Talise Palu

Abstract

Nutrition is a human's physical condition resulting from the balance of energy supplied and then released by the body. Nutrition is important to support the growth and development of babies. The period of toddlerhood is a very important period, because if the nutritional status of young children is inadequate then complications can arise in their health. The system used to determine children's nutrition is the K-nearest neighbor (KNN) method. This technique is a way to classify or group several test data whose classes are not yet known. This system uses variables based on anthropometric data or the baby's body sequence, namely childhood, child's weight, height and child's condition. The algorithm used in this research is K-NN in the child nutritional status classification system which determines whether the child's status is normal or not. The system development method used is Waterfall. According to the results of accuracy measurements, the success rate for determining the nutritional status of toddlers using this system was 79.17%