Analysis of stunting in East Java, Indonesia using random forest and geographically weighted random forest regression

Abstract

Stunting is one of the problems that the world focuses on today to be resolved immediately. World Health Organization (WHO) stipulates that a country’s public health problems are said to be chronic if the stunting prevalence rate reaches more than 20%.The prevalence rate of stunting in Indonesia in 2021 reached 24.4%. This study aims to analyze factors that correlate with the prevalence of stunting in East Java Province using machine learning methods: Random Forest Regression (RFR) and Geographically Weighted Random Forest (GWRF) methods. The results of this research are the factors that correlate with the prevalence of stunting based on the RFR method, namely the number of babies who get early breastfeeding initiation, the number of malnourished toddlers, and the number of active integrated health posts. The RFR method results in RMSE values of 3.014, MAPE 11.69%, and R2 0.8168. The factors that correlate with the prevalence of stunting based on the GWRF method are divided into six groups according to the similarity of factors that correlate with stunting in the regency/city. The GWRF method gives better results than the RFR indicated by the resulting RMSE values of 1.023, MAPE 4.45%, and R2 0.9788.