CLASSIFICATION OF TODDLER NUTRITIONAL STATUS USING A BINARY CLASSIFICATION TREE WITH ALGORITHMSQUICK, UNBIASED, EFFICENT, STATISTICAL TREE

Authors

  • Cahya Dwi Ramadhani Department of Mathematics
  • Machrani Adi Putri Siregar

DOI:

https://doi.org/10.30829/zero.v7i1.17339

Abstract

Determination of nutritional status is very important in helping to monitor the state of nutritional health growth in toddlers every time. In this study, there were 70 identity data for toddlers for the 2022 period obtained from the KB Counseling Center in the Pegajahan sub-district, in Sukasari Village. There are four independent variables used, namely gender, health insurance, weight, and height. The purpose of this study is to determine the classification that is formed and the accuracy of the resulting classification on the nutritional status of toddlers. Classification which is part of data mining can make decisions on the nutritional status of toddlers faster and more efficiently. QUEST method (Quick, Unbiased, Efficient, Statistical Trees) is one of the statistical methods that can be used to form a decision tree and classify an object using a separator algorithm that produces a binary tree. From the results of the classification there is a variable height (

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Published

2023-09-03

Issue

Vol. 7 No. 1 (2023): Zero: Jurnal Sains Matematika dan Terapan

Section

Articles

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