<![CDATA[Retail business location selection is a critical strategic decision for company success. This research aims to compare the effectiveness of the Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods in decision support systems for retail business location selection. Using a simulation-based quantitative approach, this study evaluates the performance of both methods based on alternative ranking accuracy, result consistency, and computational efficiency. Results show that AHP excels in handling complex criteria hierarchies and result consistency, while TOPSIS demonstrates superiority in computational efficiency and resilience to data outliers. Sensitivity analysis reveals that AHP is more sensitive to changes in criteria weights compared to TOPSIS. Model validation through comparison with literature case studies shows a high level of concordance between simulation results and actual decisions. This research provides theoretical contributions to the development of decision support systems and practical implications for decision-makers in the retail industry. Development prospects include method integration for hybrid approaches and exploration of big data integration in the retail location decision-making process.]]>
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