Nutrition anthtropometric status model by data mining: Case study in Palembang South Sumatera

Abstract

Children under five nutrition status has been known as an important issue in every country. Monitoring of children nutritional status should be done to overcome nutrition problem in children under five years. Anthropometric is one way to determine nutrition status by measuring weight, height/ lenght and age. Nutrition status children under five years is classified by anthropometric indices based on latest World Health Organization (WHO) criteria: Weight for age z score (WAZ), height for age z score (HAZ), weight for height z score. Data mining is a technique in computer science to give information by prediction or classification. This study proposed decision tree model which combined with anthropometric method to monitoring nutritional status of children under five. Nutrition status of children which categorized by anthropometric indices is then classified with decision tree method to monitoring nutritional status by dividing into normal or chronic. This combination could gave quick information so that can be formulated solution to overcome.