Leveraging Machine Learning Techniques for Stunting Detection and Height Growth Prediction in Children Aged 0-5 Years

Machine learning-based models are applied to classify stunting status and predict the growth of children's body length up to the age of 5 years. The Extra Trees Classifier and Random Forest Classifier algorithms are used for stunting status classification. Linear, random forest, and extra trees regression algorithms are used to predict growth. The use of this model can help early detection and effective stunting intervention. The findings highlight Random Forest's superior precision (0.834), whereas Extra Trees demonstrates a more balanced F1-score (0.836). Extra Trees Regressor performed best by obtaining an MSE of 12.4, MAE of 2.64, and R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>-Score of 0.95.