Spatial Autocorrelation Analysis to Identify Hotspots of Stunting Cases in Kerinci Regency

Abstract

There has been a reduction in prevalence of stunting nationally, the prevalence is still high in several regions, including Kerinci Regency. This study focused on identifying hotspots for stunting cases in Kerinci Regency, Jambi Province, utilizing spatial autocorrelation analysis. The research aimed to pinpoint specific regions with high prevalence of stunting in 2019, 2020, and 2021, highlighting the importance of tailored interventions at the village level to combat stunting effectively. This research utilized data on stunting cases sourced from the community-based nutrition recording and reporting system (e-PPGBM) from 2019 to 2021. Spatial autocorrelation analysis was conducted using the global and local indicator for spatial auto correlation (LISA) with village as the analysis unit. This study found the Moran Index values in 2019, 2020, and 2021 were 0.148, 0177, and 0.238 respectively. Hotspots were found in specific regions of the regency in each year, with shifts in distribution patterns observed. In 2019, hotspots were in the southwest region, in 2020 in the central part, and in 2021 in the southwest region. These findings highlight the importance of targeted interventions at the village level to address issues effectively. Continued monitoring and targeted efforts are crucial to address the shifting patterns and improve the overall nutritional status of the population.