PEMODELAN PERTAMBAHAN TINGGI BADAN BALITA STUNTING MENGGUNAKAN METODE REGRESI TOBIT KUANTIL BAYESIAN BOOTSTRAP - Khatimah, Havifah Husnatul; Yanuar, Ferra; Devianto, Dodi (Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 2025)
The purpose of this study was to analyze the model of height increase in stunted toddlers in West Sumatra Province and the factors that influence it using the Bayesian tobit quantile regression method. Then the parameters of the resulting model will be tested for accuracy using the Bootstrap method. The data used in this study are secondary data in the form of data on the height of stunted toddlers in West Sumatra Province obtained from the West Sumatra Health Office in August 2021 and February 2022 for 1755 toddlers. After analyzing the data on the height increase in stunted toddlers using the Bayesian tobit quantile regression method, it was found that the model at quantile 0.50 was the best model because it produced smaller MAD and RMSE values ​​than other quantiles. Furthermore, the parameter estimation of the Bayesian tobit quantile regression model has produced an acceptable estimated value because it is within the Bootstrap confidence interval. The significant factors influencing the height increase in stunted toddlers in West Sumatra Province are exclusive breastfeeding and immunization.