Murien Nugraheni
Program Studi Teknik Informatika Universitas Ahmad Dahlan Yogyakarta Jl. Prof. Dr. Soepomo, S.H., Warungboto, Janturan, Yogyakarta 55164 Telp : (0274) 563515 ext. 3208

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Infotech: Journal of Technology Information

ANALISIS PREDIKSI TUMBUH KEMBANG ANAK DENGAN MACHINE LEARNING Nugraheni, Murien; Widodo, Widodo; Lestari, Uning; Effendy, Vina Ardelia; Yunanto, Prasetyo Wibowo; Amannu, Ramadhan
Infotech: Journal of Technology Information Vol 11, No 1 (2025): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i1.389

Abstract

Stunting is a major chronic nutritional issue that remains a significant challenge in Indonesia. This study aims to predict the risk of stunting in children and enhance prevention efforts by analyzing the health and nutritional status of parents. The research employs Machine Learning methods by comparing the performance of the Decision Tree and Gaussian Naive Bayes algorithms. The dataset was obtained from open data sources and analyzed using Google Colab, with a Technology Readiness Level (TRL) of level 3. Evaluation results show that both algorithms achieved an accuracy of 95.35% based on the confusion matrix. The model accurately identified 2 stunting cases (True Positive) and 41 non-stunting cases (True Negative), indicating a high level of classification reliability. These findings suggest that Machine Learning approaches can be effectively utilized as early detection tools to support stunting prevention strategies in children.