Identification of Toddlers' nutritional status using data mining approach

Abstract

One of the problems in community health center or health clinic is documenting the toddlers' data. The numbers of malnutrition cases in developing country are quite high. If the problem of malnutrition is not resolved, it can disrupt the country's economic development. This study identifies malnutrition status of toddlers based on the context data from community health center (PUSKESMAS) in Jogjakarta, Indonesia. Currently, the patients' data cannot directly map into appropriate groups of toddlers' malnutrition status. Therefore, data mining concept with k-means clustering is used to map the data into several malnutrition status categories. The aim of this study is building software that can be used to assist the Indonesian government in making decisions to take preventive action against malnutrition.