Spatio-temporal modeling to identify factors associated with stunting in Indonesia using a Modified Generalized Lasso.

This study investigates the factors associated with stunting prevalence in Indonesia, utilizing a generalized lasso framework with modified penalty matrices to accommodate spatio-temporal data structures. Novel approaches are introduced to construct the penalty matrices, with particular focus on defining neighborhood structures. The proposed method is applied to data from 34 Indonesian provinces, covering the years 2019 to 2023.