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Jurnal Bina PrajaJurnal Bina Praja

Stunting in toddlers is a significant nutritional issue that may negatively impact the quality of Indonesias future human resources. This study aims to analyze the spatial patterns of stunting prevalence in toddlers in Indonesia as a basis for developing region-based policy interventions. A quantitative approach was used through spatial autocorrelation analysis using Morans I Index and Local Indicators of Spatial Autocorrelation (LISA), which is based on the K-Nearest Neighbors (KNN) method. Stunting prevalence data were obtained from 514 districts/cities in Indonesia and analyzed to detect clustering patterns in high-risk areas. The results showed a Morans I of 0.315 (P-value <), indicating positive spatial autocorrelation among regions. Also, these results indicate that areas with high stunting prevalence tend to be geographically clustered, particularly in areas outside Java, such as Nusa Tenggara, Kalimantan, Sulawesi, and Papua. The results of this study emphasize the importance of a region-based approach to stunting management that accounts for spatial factors. High-high cluster areas are highly vulnerable to stunting, as indicated by low nutrition coverage, access to sanitation, and protein consumption, as well as high poverty rates. This situation highlights the importance of more focused and effective policy interventions that include improving nutrition, increasing access to food and sanitation, health education, and strengthening welfare and education aspects.

The spatial analysis of stunting prevalence in Indonesia in 2024 revealed a significant positive spatial autocorrelation pattern between districts/cities, indicating that areas with high stunting prevalence tend to be geographically close to each other.The LISA analysis identified 32 districts/cities as falling into the “high-high cluster category, concentrated in regions outside Java like Kalimantan, Nusa Tenggara, Sulawesi, and Papua.These findings underscore the importance of implementing place-based policy strategies that respond to specific local and spatial characteristics to effectively reduce stunting prevalence.

Further research should investigate the specific local factors driving stunting within the identified high-high clusters, such as detailed analyses of household food security, access to healthcare, and sanitation practices, to inform targeted interventions. Additionally, studies are needed to evaluate the effectiveness of different intervention strategies in spatially clustered areas, considering the potential for spillover effects between neighboring regions. Finally, research should explore the role of governance and inter-sectoral coordination in addressing stunting, focusing on how to strengthen collaboration between local governments, health agencies, and community organizations to implement comprehensive and sustainable stunting reduction programs. These investigations should also consider the impact of climate change and environmental factors on food availability and nutritional status in vulnerable regions, and how these factors interact with existing socio-economic determinants of stunting.

  1. Childhood stunting: a global perspective - Onis - 2016 - Maternal & Child Nutrition - Wiley Online... onlinelibrary.wiley.com/doi/10.1111/mcn.12231Childhood stunting a global perspective Onis 2016 Maternal Child Nutrition Wiley Online onlinelibrary wiley doi 10 1111 mcn 12231
  2. A review of child stunting determinants in Indonesia - Beal - 2018 - Maternal & Child Nutrition -... onlinelibrary.wiley.com/doi/10.1111/mcn.12617A review of child stunting determinants in Indonesia Beal 2018 Maternal Child Nutrition onlinelibrary wiley doi 10 1111 mcn 12617
  3. Moran’s I Index and KKN-Based LISA: Spatial Analysis of Toddler Stunting in Indonesia 2024 | Jurnal... doi.org/10.21787/jbp.17.2025-2888MoranAos I Index and KKN Based LISA Spatial Analysis of Toddler Stunting in Indonesia 2024 Jurnal doi 10 21787 jbp 17 2025 2888
  4. Spatial clustering of stunting cases in Indonesia: A Bayesian approach | Azis | Commun. Math. Biol. Neurosci..... scik.org/index.php/cmbn/article/view/7898Spatial clustering of stunting cases in Indonesia A Bayesian approach Azis Commun Math Biol Neurosci scik index php cmbn article view 7898
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