Penerapan Algoritma C4.5 Pada Klasifikasi Status Gizi Balita

Authors

  • Yusuf Ramadhan Nasution Universitas Islam Negeri Sumatera Utara
  • Armansyah Universitas Islam Negeri Sumatera Utara
  • Mhd Furqan Universitas Islam Negeri Sumatera Utara
  • Toibatur Rahma Matondang Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.37859/jf.v14i1.6941
Keywords: Machine Learning, C4.5 Algorithm, Nutritional Status of Toddlers, Classification, RapidMiner

Abstract

The study aims to classify the nutritional status of the child using the C4.5 algorithm. The secondary data used is derived from the assessment of the nutrition status of a child in Puskesmas Promji and Puksesmas Suka Makmur. A classification model is constructed using the C4.5 algorithm based on a number of predictor factors that have been determined. The research methodology includes data collection, data preprocessing, model development with C4.5 algorithms, model evaluation, and results analysis. Model evaluation is done using measurements such as accuracy. In addition, the significance of predictor variables in affecting the nutritional status of infants was also evaluated through data analysis. This research contributed to the development of a method of classifying the nutritional status of infants using the C4.5 algorithm approach. The implication of this study is that the classification model developed can be used as a tool to support early identification and intervention against nutritional problems in infants. Furthermore, based on testing using the confusion matrix technique with the 80:20 data division of a total of 502 datasets, consisting of 402 training data and 100 testing data, an accuracy rate of 80 percent was obtained.

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Published

2024-04-30

Issue

Vol. 14 No. 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)

Section

Articles

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