<![CDATA[Sustainable regional development in Semarang City faces challenges regarding unmapped social welfare disparities and uneven infrastructure distribution across its 16 districts. Conventional assessment methods often suffer from subjective bias and fail to capture multidimensional data complexity, potentially leading to misallocated resources. This research aims to objectively analyze and rank district welfare levels using a Decision Support System (DSS) approach, assisting local government in accurately prioritizing development strategies. The systematic research stages encompass problem identification, dataset collection, objective weighting using the Entropy method, alternative ranking using the Evaluation Based on Distance from Average Solution (EDAS) method, and final result analysis. The hybrid framework utilizes Entropy to determine objective weights for five critical criteria (number of households, population size, healthcare facilities, stunting cases, and school facilities) based on data variation, eliminating human error. Meanwhile, EDAS evaluates district performance by calculating positive and negative distances from the average solution. Results reveal sharp inequality; Pedurungan District achieved the top rank (0.935), reflecting an optimal balance between public facilities and population needs. Conversely, Semarang Utara District ranked last (0.058), primarily driven by high stunting incidence as a major cost factor. The integrated Entropy-EDAS model provides a robust scientific basis for policymakers to effectively target budget allocation and stunting reduction programs in disadvantaged areas.]]>
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