<![CDATA[Determining the priority of assistance for children under two years old (Baduta) is a crucial step in accelerating stunting reduction programs. However, in practice, this process is still conducted manually, leading to potential subjectivity and inaccurate targeting. This study aims to implement the Simple Additive Weighting (SAW) method within a Decision Support System to determine the priority of Baduta assistance in Kediri City in an objective and systematic manner. The dataset consists of 300 Baduta, evaluated based on criteria including body weight, height, attendance at community health posts, and access to health service referrals. Preliminary results indicate that the normalization process successfully transformed the data into a standardized scale (0–1), enabling proportional comparison across all criteria. The weighting process shows that height and body weight have dominant contributions to the preference value calculation. The final results demonstrate that the system produces preference values ranging from 0.46 to 0.83, where lower values indicate higher priority for assistance. Furthermore, the system successfully identifies the top 10 priority Baduta as the primary targets for intervention. The implementation of the system also improves decision-making efficiency compared to manual methods and produces more consistent and objective rankings. The main contribution of this study lies in the integration of the SAW method into a dashboard-based system to support more accurate and measurable decision-making for prioritizing Baduta assistance.]]>
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