Design and implementation of a product comparison system using multi-criteria decision making analysis based on rest api

In this thesis, a decision support system capable of performing comparative analysis of products offered in online shopping environments using Multi-Criteria Decision Making (MCDM) methods has been designed and developed. The system was implemented in accordance with RESTful architectural principles, coded using PHP, and integrated with a MySQL database for data management. Users can evaluate alternative products based on their specified criteria and associated weights, obtaining data-driven results to support the decision-making process. The system incorporates the CRITIC method for objective weight determination, the TOPSIS method for ranking alternatives based on proximity to the ideal solution, and the ELECTRE method for dominance analysis through pairwise comparisons. The API exchanges data in JSON format and can operate with either manually defined or system-generated weights, offering flexibility and transparency to the user. During the implementation phase, the developed API was tested using a client interface. The analysis results were returned as JSON outputs and visualized through directed graphs. With its scalable, modular, and extensible architecture, the system is suitable for deployment across various industries. In particular, it provides effective decision-making support in areas such as e-commerce, supply chain management, and service quality evaluation. As a result, the developed RESTful API-based system has proven to be a successful solution in terms of both technical accuracy and decision support capability. Furthermore, the proposed system has the potential to evolve into a comprehensive decision support platform through the integration of additional methods and user interface enhancements in the future.