<![CDATA[This study proposes a web-based decision support system for woven fabric selection by integrating the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA). The system addresses limitations in conventional selection processes that rely on subjective judgment and lack structured multicriteria evaluation. The proposed approach combines uncertainty-based weighting using Fuzzy AHP with objective ranking using MOORA, enabling a transparent and systematic decision-making process. Unlike previous hybrid MCDM-based recommender systems, this study integrates user preference modeling within a web-based framework and incorporates consistency validation and sensitivity analysis to ensure reliable results. The experimental results show that fabric type is the most influential criterion, with a weight of 0.33, and that alternative A4 consistently ranks as the best option, with an optimization value of 0.392. Sensitivity analysis shows that the ranking results remain stable across a 20% weight variation, and comparison with the SAW method confirms consistent rankings. In addition, User Acceptance Testing (UAT) involving 20 respondents achieves a score of 86.4%, indicating high usability and user satisfaction. However, the system is evaluated within a limited dataset and does not incorporate adaptive learning mechanisms. Therefore, future work is directed toward expanding the dataset and integrating machine learning-based approaches to enhance adaptability and scalability. Overall, the proposed system provides a structured, transparent, and empirically validated solution for multicriteria decision-making.]]>
