<![CDATA[This study compares the Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods for determining the best teacher at SMK Swasta PABAKU Stabat. Teacher data was collected from 19 individuals via observation, interviews, and literature review. The web-based decision support system built successfully integrated SAW and TOPSIS to select the top teacher. SAW produced rankings more aligned with manual rankings, boasting 53% accuracy, while TOPSIS yielded 32% accuracy. Additionally, SAW averaged a faster 0.10672 second execution time, contrasted to TOPSIS requiring 0.57004 seconds. Overall, this research offers meaningful insight into the effectiveness and efficiency of applying SAW and TOPSIS for best teacher selection. With superior accuracy and speed, SAW proves the more fitting and appropriate choice of the two methods. REFERENCES [1] M. Kholis, K. Wicaksono, and R. 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