A Robust Multi-Criteria Decision Support Framework Using WASPAS For Transparent and Efficient Cooperative Ranking

Cooperatives play a critical role in promoting inclusive economic development and strengthening community-based financial systems. However, the evaluation of cooperative performance remains a challenging task, particularly when traditional assessment processes rely on manual procedures that are time-consuming, inefficient, and prone to subjectivity. This study proposes a data-driven Decision Support System (DSS) based on the Weighted Aggregated Sum Product Assessment (WASPAS) method to enhance the objectivity, accuracy, and efficiency of cooperative performance evaluation. The proposed approach integrates the Weighted Sum Model (WSM) and the Weighted Product Model (WPM), enabling a more robust multi-criteria decision-making framework. The evaluation is conducted using seven key financial and operational indicators, including the number of members, capital, Return on Equity (ROE), Net Profit Margin (NPM), Return on Assets (ROA), Debt to Asset Ratio (DAR), and Debt to Equity Ratio (DER). The system is developed using a prototyping methodology and implemented through a web-based platform utilizing PHP and MySQL. To ensure system reliability and performance, comprehensive testing was conducted, including black-box testing and sensitivity analysis of the weighting parameter (λ). The results indicate that λ = 0.5 produces the most stable and consistent ranking outcomes, demonstrating the robustness of the proposed model. The findings confirm that the proposed WASPAS-based DSS significantly improves the transparency, consistency, and computational efficiency of cooperative evaluation compared to conventional manual approaches. This study contributes to the development of intelligent decision-making systems for cooperative management and provides a scalable framework for performance assessment in similar socio-economic institutions.