<![CDATA[Choosing a strategic store location is an important factor in retail business success, but this decision is often influenced by data uncertainty and scale differences among criteria that can lead to bias in the decision-making process. This study proposes the use of LOPCOW to objectively determine the criterion weights based on data variability among alternatives, and AROMAN to reduce the influence of scale differences among criteria through gradual normalization. With this approach, it is hoped to obtain a more accurate, fair, and consistent ranking of locations. The ranking results in the selection of retail store locations are based on the final value of each alternative location. The location with the code LKM ranks highest with a final value of 0.8212, indicating that this location has the most optimal characteristics compared to other locations. The results of the study show that the combination of these two methods can produce more optimal and reliable decisions in selecting retail store locations, which in turn can enhance competitiveness and operational success in the retail business. The contribution from the ranking results of this retail store location provides significant strategic insights in the decision-making process for business expansion. By leveraging a quantitative approach that generates a final value for each location alternative, this research is able to provide an objective foundation for managers or decision-makers in selecting the best location. The identification of LKM locations as the most superior alternative indicates that the evaluation method used is effective in revealing the competitive advantages of a location based on the established criteria.]]>
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