Classification System Of Toddler Nutrition Status using Naïve Bayes Classifier Based on Z- Score Value and Anthropometry Index

Abstract

The system of nutritional status assessment for a toddler is crucial to monitor the growth of a toddler. This present study was carried out to build a classification system for determining the assessment of toddler nutritional status using naive bayes classifier based on value the z-score and index of Anthropometry. The data was used to perform classification include gender, age, height and weight. The data was calculated using the z-score to get nutritional status based on anthropometric indices-weight-for-age, height-for-age, weight-for-height for classified use Naive Bayes Classifier. This study used 225 data of toddlers. Testing system used 55 data as training and 175 data as testing with 100% accuracy. The results of this study was a system that could be used to perform classification of nutritional status based on a combination of three anthropometric indices using the Naive Bayes Classifier. Naive Bayes Classifier performed classification interpretation of nutritional toddler consisting of malnutrition, normal and over-nutrition. This study showed that the classification of nutritional status was on 175 data generating the highest percentage was malnutrition of 44.58%.