<![CDATA[This study aims to evaluate the effectiveness and efficiency of the SAW and TOPSIS methods in decision support systems and identify the latest trends and innovations in their application. The research analyzes various academic sources, including journals and conference papers, that discuss these methods and compare them with other approaches based on criteria such as accuracy, complexity, and ease of implementation. Case studies from different fields are utilized to assess the real-world performance of these methods. The findings indicate that the SAW method is more efficient in computational time and suitable for problems with numerous quantitative criteria, although it is less optimal for criteria with highly varied importance levels. Meanwhile, the TOPSIS method provides higher accuracy in handling diverse criteria and complex data, albeit requiring more time and computational resources. Both methods remain relevant due to innovations that enhance their effectiveness in various decision support system applications.]]>
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