Metode K-Nearest Neighbor Dan Naive Bayes Dalam Menentukan Status Gizi Balita

Abstract

The nutritional intake needed by toddlers during the growth period for each individual has a different amount of consumption, therefore a process of checking nutritional status must be carried out. The indicators high and weight that will be calculated in determining the nutritional status. Until now the process of it status children under five is still carried out manually, resulting in the classification process of nutritional not being as expected. It is difficult for parents to go to the health center to check on their child's condition because the location is far from where they live and the administrative process is long. The propose is website-based information system, as well as providing recommendations on which method is the most accurate among K-Nearest Neighbors and Naïve Bayes in determining the nutritional status of toddlers. The results of this study have succeeded in creating an information system that can be used by users by inputting condition criteria for the process of classifying the nutritional status of toddlers. Naïve Bayes method is superior with a percentage value of 87.5% while the K-Nearest Neighbor method with k = 3 has an accuracy percentage of 71.25%