• Izzati Rahmi Department of Mathematics and Data Science Faculty of Mathematics and Natural Science, Andalas University, Indonesia
  • Yana Wulandari Department of Mathematics and Data Science Faculty of Mathematics and Natural Science, Andalas University, Indonesia
  • Hazmira Yozza Department of Mathematics and Data Science Faculty of Mathematics and Natural Science, Andalas University, Indonesia
  • Mahdhivan Syafwan Department of Mathematics and Data Science Faculty of Mathematics and Natural Science, Andalas University, Indonesia
Keywords: Nutritional Status, Rough Set Algorithm, Decision rules, Inconsistencies


The health and nutrition of children at the age of five are very important aspects in the children’s growth and development. An assessment of the nutritional status of toddlers that is commonly used is anthropometry. This study aims to obtain the decision rules used to classify toddlers into nutritional status groups using the rough set algorithm and determine the level of classification accuracy of the resulting decision rules. The index used in this study is the weight-for-age index. Attributes used in this study were the mother’s education level, mother’s level of knowledge, the status of exclusive breastfeeding, history of illness in the last month, and nutritional status of toddlers. The results of the analysis show that there are 21 decision rules. In this study, the resulting decision rules experience inconsistencies. The selection of decision rules that experience inconsistencies is based on each decision rule’s highest strength value.  The rough set algorithm can be used for the classification process with an accuracy rate of 86.36%.


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How to Cite
I. Rahmi, Y. Wulandari, H. Yozza, and M. Syafwan, “CLASSIFICATION OF TODDLER’S NUTRITIONAL STATUS USING THE ROUGH SET ALGORITHM”, BAREKENG: J. Math. & App., vol. 17, no. 3, pp. 1483-1494, Sep. 2023.