Stunting is a chronic nutritional deficiency and can have long-term impacts that are detrimental to health in the next life cycle. In 2021 the stunting rate in Indonesia will be 24.4 percent. The prevalence rate of stunting in each province varies so it is suspected that there are regional proximity and characteristics that contribute to the prevalence of stunting. This research aims to predict stunting by considering regional proximity in Indonesia. The research design is cross-sectional. The analysis used is spatial Geographically Weighted Regression (GWR) to predict stunting risk factors by considering regional proximity in the analysis. Research data uses secondary data from the 2021 Indonesian Nutrition Status Study (SSGI). The observation units are 34 provinces in Indonesia. GWR analysis uses Kernel Fixed Gaussian weights (smallest AIC value). The results of the analysis found that the GWR model is better used to model the determinant factors of toddler stunting in Indonesia compared to the OLS/linear regression model. Four predictor variables influence stunting, namely the proportion of the population who have JKN/Jamkesda, the proportion of sick toddlers who undergo examination/treatment at health service facilities, the proportion of toddlers with low birth weight categories, and the proportion of toddlers who experience diarrhea.
Copyrights © 2023