Application of the Naïve Bayes Algorithm and Radipminer Application to Determine the Nutritional Status of Toddlers

Abstract

Determining the nutritional status of toddlers is an important activity carried out by medical personnel at community health centers as technical implementers. Because with the results of determining nutritional status, intervention efforts to overcome the condition of toddlers who experience malnutrition, malnutrition or overnutrition can be addressed as early as possible. However, medical personnel often find it difficult to determine the nutritional status of toddlers due to limited human resources and equipment, so it is important to have a method used to determine the nutritional status of toddlers quickly, precisely and accurately. For this reason, in this study we used the Naïve Bayes algorithm in calculating the classification for determining the nutritional status of toddlers. The research results show that the Naïve Bayes algorithm can increase the level of data accuracy in determining the nutritional status of toddlers with a data accuracy value of 70.33%