Penerapan Algoritma Naive Bayes Untuk Penentuan Balita Penerima Makanan Tambahan (PMT) Berdasarkan Status Gizi Di Pos Pelayanan Terpadu

Abstract

This study aims to determine toddlers who are classified as toddlers who are eligible to receive assistance as recipients of additional food (PMT) based on the nutritional status of toddlers. A toddler does not get nutrition in a balanced amount, malnutrition can occur, and the toddler himself will have stunted growth, so the problem I raised is that toddlers who are affected by malnutrition will be assisted by the Health and Posyandu in the Supplementary Feeding program (PMT) so that the nutrition of infants affected by malnutrition can be assisted in their recovery. This research was carried out from April to June 2022, located at Posyandu Melati, Kelurahan Margatunggal, Kecamatan Jayaloka, Musi-Rawas, South Sumatra. In this research, an application is made that can provide determination of eligible toddlers as recipients of additional food (PMT) to minimize errors in choosing toddlers who deserve this assistance by applying the Naive Bayes method. The variables used were based on the nutritional status of toddlers such as gender, nutritional status, weight based on age, nutritional status, height based on age, nutritional status, weight based on height, status of toddlers receiving additional food. % and is interpreted as very feasible while the results of the user eligibility percentage are 88.48%, then related to the application made can be categorized into a very feasible interpretation. And an accuracy test has also been carried out using a confusion matrix with 96% accuracy results.