Modeling Stunting Prevalence in Districts and Cities on Java Island
Keywords:
Stunting, Smoothing Spline, Nonparametric Regression, Generalized Cross ValidationAbstract
Stunting is a chronic nutritional problem that remains a major concern in Indonesia, particularly on the island of Java, which accounts for a significant proportion of cases nationwide. Poverty and inadequate food intake are known to be associated with the prevalence of stunting, but the relationship between these variables is not always linear. This research seeks to apply a smoothing spline approach within a nonparametric regression framework to examine the association between stunting prevalence, poverty levels, and the proportion of households experiencing inadequate food consumption across regencies and cities on Java in 2024. The data used consisted of 119 observations, divided into 80% training data and 20% testing data. Model estimation was carried out through a penalized least squares framework, and the smoothing parameter was obtained using the GCV approach. The results show that the optimal parameters were obtained at a combination of λ₁ = 16681 and λ₂ = 464.15 with a minimum GCV value of 25.2396. An MSE value of 28.75 indicates that the model is capable of modeling the relationship between predictor variables and stunting prevalence. The R-squared coefficient of 0.2446 indicates that 24.46% of the variation in stunting prevalence can be explained by the model. Thus, spline smoothing regression is effective in capturing nonlinear relationship patterns in stunting data on the island of Java.
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