Stunting is a chronic nutritional problem that affects the growth and development of children in developing countries, including Indonesia. The prevalence of stunting in Indonesia in 2023 reached 21.5%, with East Nusa Tenggara (NTT) Province recording a significantly high rate of 37.9%. This study aims to analyze the factors influencing stunting among children under five in NTT Province in 2023 using the Finite Mixture Partial Least Square (FIMIX-PLS) approach. The factors analyzed include healthcare services, socioeconomic conditions, environment, and immunization. The data analysis technique involved modeling using Partial Least Squares-based Structural Equation Modeling (PLS-SEM), beginning with construct validity and reliability testing, followed by data segmentation using FIMIX-PLS to identify heterogeneity and classify districts/cities based on the pattern of relationships among latent variables. The results of the analysis indicate the presence of data heterogeneity across regions, with several indicators showing significant variation between areas. These findings are expected to provide deeper insights into the contributing factors of stunting and assist in formulating more effective policies to reduce stunting rates in NTT.
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