<![CDATA[Background: The high rate of drug abuse in East Java Province indicates a complex socioeconomic issues that are region-based. This can be seen from the uneven distribution of drug abuse cases, which is thought to be influenced by regional socioeconomic conditions. A spatial approach, specifically spatial autocorrelation analysis, is needed to identify clustering patterns and interregional connections. Objective of this study to identify the areas in East Java with the highest risk of drug abuse rates from 2019 to 2023. Methods: This is an observational study with a cross-sectional design using spatial autocorrelation analysis. The population and sample consist of 38 regencies/cities in East Java Province from 2019 to 2023, with a total sampling technique. Results: There was spatial autocorrelation in drug abuse cases with positive and significant Moran's I value over five years. There was spatial autocorrelation in the variables of minimum wage, crime rate, and open unemployment rate in relation to drug abuse cases with positive and significant Moran's I value over five years. Conclusion: There is spatial autocorrelation in the variables of minimum wage in regencies/cities, crime rates, and open unemployment rates in relation to drug abuse cases in East Java Province from 2019 to 2023. Conclusion: the results of this study can be used as a basis for policy formulation focusing on areas with high wages, high crime rates, and high unemployment rates regarding region-based drug abuse interventions so that integrated interventions can be carried out.]]>
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