SISTEM PAKAR DETEKSI GIZI BURUK BALITA DENGAN METODE NAÏVE BAYES CLASSIFIER

Abstract

Malnutrition is a disease with a growing number of sufferers every year in Indonesia. The percentage of malnutrition in Indonesia is around 3.4%. The characteristics of malnutrition indicate that growth is not optimal, intellectual development is not optimal, the appearance of visual impairment, fatigue, lack of appetite, abnormal bone shape, easy pain. The limited number of medical personnel can be assisted by the application of an expert system without intending to replace the Expert. Expert system is a system (knowledge machine) that is able to replace the function of expertise. This study aims to detect malnutrition at the age of 1-3 years (toddlers). using the Naïve Bayes Clasifier algorithm. In this study known 3 types of diseases based on symptoms, namely Kwarshiorkor (P1), Marasmik-Kwarshiorkor (P2), Marasmus (P3) with 24 symptoms of malnutrition. The results showed the highest multiplication results from the naive bayes classification were a type of malnutrition suffered by patients. Detection results can be used as initial information on the detection of malnutrition.