<![CDATA[The development of decision support systems has become essential in assisting businesses to make accurate and objective decisions, especially in product selection processes. However, many retail businesses still rely on manual decision-making, which is often subjective and inconsistent. This study aims to develop a decision support system using the Analytical Hierarchy Process (AHP) and Multi-Factor Evaluation Process (MFEP) methods to improve the accuracy and consistency of product recommendations. The AHP method is used to determine the weight of each criterion through pairwise comparisons, while the MFEP method is applied to evaluate and rank product alternatives based on these weights. The criteria used in this study include sales, profit, and customer preferences. Data collection was conducted through observation, interviews, and documentation. The results show that the system is able to generate structured and objective product rankings. The highest score obtained is 4.6, indicating the most recommended product alternative. Furthermore, the evaluation results show that the system achieves an accuracy of 92% and a precision value of 90%, indicating high relevance of the recommendations. In addition, the Spearman Rank Correlation value of 0.95 indicates a very strong agreement between the system results and expert judgment. Therefore, the proposed system is effective in improving decision-making accuracy, reducing subjectivity, and providing reliable product recommendations.]]>
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