MODEL PREDIKSI PREVALENSI STUNTING DI PROVINSI ACEH MENGGUNAKAN PENDEKATAN REGRESI DENGAN EVALUASI KINERJA BERBASIS MSE DAN RMSE - Novia Hasdyna (Universitas Dharmawangsa, 2025)
This study aims to develop a predictive model for stunting prevalence in Aceh Province using regression-based approaches, including Linear Regression, Polynomial Regression, Ridge Regression, and Lasso Regression. The dataset comprises stunting prevalence rates from 2019 to 2023 across 21 districts and cities in Aceh Province. The analysis projects prevalence trends up to 2031 and evaluates the model performance using Mean Squared Error (MSE) and Root Mean Squared Error (RMSE). The results indicate that Polynomial Regression demonstrates the best predictive performance, with an average MSE of 0.0012 and RMSE of 0.0317, outperforming Linear Regression (MSE = 0.0039, RMSE = 0.0621), Ridge Regression (MSE = 0.0187, RMSE = 0.1324), and Lasso Regression (MSE = 0.0039, RMSE = 0.0621). The prediction results suggest a gradual decline in stunting prevalence across Aceh Province up to 2031, with an average annual decrease of approximately 1.2%. Therefore, Polynomial Regression can be considered a reliable and accurate model for analyzing and forecasting regional stunting prevalence trends.