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All Journal International Journal of Applied Sciences and Smart Technologies
Yanuarius Basilius
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Computer Science & IT Energy Engineering Industrial & Manufacturing Engineering

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Classification of Toddler Nutrition Using C4.5 Decision Tree Method Kartono Pinaryanto; Robertus Adi Nugroho; Yanuarius Basilius
International Journal of Applied Sciences and Smart Technologies Volume 03, Issue 01, June 2021
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v3i1.3366

Abstract

Nutrition is very much needed in the growth of toddlers. It is very important to give babies a balanced nutritional intake at the right stage so that the baby grows healthy and is accustomed to a healthy lifestyle in the future. Children under five years of age are a group that is vulnerable to health and nutrition problems. In determining the nutritional status, it can be done in a system manner using the C4.5 decision tree classification method and entering several variables or attributes. The dataset tested was 853 toddlers. Classification is carried out to determine the nutritional status based on the weight/age (BB/U), height/age (TB/U) and weight/height (BB/TB) categories. The attributes used for the classification of BB/U are gender, weight and age. The attributes used for TB/U are gender, body length or height, and age. The attributes used for BB/TB are gender, weight, body length or height, and age. The average accuracy of the BB/U category is 90.16%, the average accuracy of the TB/U category is 76.64%, and the average accuracy of the BB/TB category is 83.83%.
Co-Authors Kartono Pinaryanto Robertus Adi Nugroho