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Abstract Objectives To find stunting hotspots district/ cities in Indonesia in seven major islands in Indonesia. Method This is an ecological study that using aggregate data. We used data from The Basic Health Research Report of Indonesia 2018 and The Poverty Data and Information Report from the Central Bureau of Statistics (BPS) 2018. We analyzed 514 districts/ cities in Indonesia that spread out in 7 major Islands with 34 provinces. We used The Euclidean distance method to determine the neighborhood. Moran’s test was occupied to identify autocorrelation while Moran’s Scatter Plot particularly in the high-high quadrant was used to identify stunting hotspot areas. Result It was found that there is autocorrelation among districts/ cities in four major islands namely Sumatera, Java, Sulawesi, and Bali Nusa Tenggara Timur (NTT) Nusa Tenggara Barat (NTB). We identified 135 districts/ cities as stunting hotspot areas that spread in 14 provinces in four islands. Conclusion There is autocorrelation among districts/ cities in Sumatera, Java, Sulawesi, and Bali NTT NTB which resulted in 135 districts/ cities identified as stunting hotspots in four major islands in Indonesia Policy implication Provide information to the government in prioritizing stunting prevention areas in Indonesia in term of the acceleration of stunting prevention. Summary Strengths and limitations of this study: The hypothesis which states that the prevalence of stunting in one area is associated with the prevalence of stunting in the neighboring area is a new method that should be considered to set the policy. The study results can be used by the government to set priority areas for stunting interventions in Indonesia because so far, the government has made priorities based on stunting prevalence and weighted by poverty. Thus, by setting the priority areas, the funds required will be less compare if it executed in districts of Indonesia simultaneously. The weakness in this study is the geographical differences of Indonesia regions given the vastness of the Indonesian territory. Some of the districts are separated by oceans and the size of the area is sometimes extremely different. It becomes difficult in determining the neighborhood definition method. Some regions will have no neighbors under certain conditions. Therefore, further research can be carried out with different methods of neighborhood definition.
Sipahutar et al. (Tue,) studied this question.