IMPLEMENTATION OF THE C4.5 DECISION TREE ALGORITHM ON THE NUTRITIONAL STATUS OF TODDLERS (CASE STUDY: POSYANDU "ABC”)
Keywords:
Posyandu, Malnutrition, News, Prevention, Countermeasures, DecisionTree, AlgorithmC4.5.Abstract
Malnutrition is a serious health problem in children under five in Indonesia. Posyandu (Integrated Service Post) has an important role in the prevention and control of malnutrition. This study aims to evaluate the role of Posyandu in the prevention and management of malnutrition in toddlers. Posyandu can also make referrals to higher health facilities if cases of malnutrition are found. The purpose of this study will be to test the nutritional status classification model of toddlers at Posyandu "ABC" by utilizing data mining techniques using the Decision Tree method of the C4.5 Algorithm. The results of the study show that the criteria of Age, Weight, Height and Parental Nutrition Knowledge play a role in monitoring the growth and development of toddlers, early detection of malnutrition, and providing nutrition education to mothers under five. Thus, the results of this study can be one of the strategies in preventing and overcoming malnutrition status in toddlers in Indonesia.
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