<![CDATA[Selecting the best students in the robotics extracurricular program at SD Madinah Slawi is an important process for identifying outstanding participants eligible to represent the school in various activities and competitions. The current manual assessment process requires considerable time and may introduce subjectivity into decision-making. This study aims to implement the Simple Additive Weighting (SAW) method in a decision support system to assist the selection process objectively, efficiently, and accurately. A quantitative research method was employed, with data collected through observation, interviews, and documentation. The data comprised 228 robotics extracurricular students assessed using five criteria: knowledge score, skill score, activeness, attendance, and attitude. Data processing included determining criterion weights, constructing the decision matrix, normalizing the data, and calculating preference values using the SAW method. The results showed that SAW successfully generated objective student rankings based on the preference values of each alternative. The study focused on selecting the top 10 students. The highest preference value was 0.88, while the lowest was 0.81. Implementing the SAW method assisted extracurricular supervisors in decision-making, improved assessment efficiency, and produced more objective, transparent, and consistent decisions than the manual assessment process.]]>
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