IMPLEMENTATION OF THE MOORA METHOD IN A DECISION SUPPORT SYSTEM (DSS) FOR DATA-DRIVEN SELECTION OF RESEARCH GRANT RECIPIENTS

The process of determining research grant recipients for lecturers plays an important role in supporting the improvement of research quality in academic environments. However, research grant selection that is still carried out manually may lead to several challenges, particularly in the evaluation process and the management of assessment data. Therefore, this study is conducted within the context of research grant management at the Institute for Research and Community Service (LPPM) of Universitas Muhammadiyah Kalimantan Timur (UMKT). This study aims to apply the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to a data-driven Decision Support System (DSS) to support the research grant selection process. A quantitative applied approach is used by utilizing secondary data, including research grant proposal data, assessment criteria along with their weights, and reviewer evaluation results obtained from LPPM UMKT. The implementation of the MOORA method is carried out through several stages, namely the construction of a decision matrix, data normalization, criteria weighting, optimization value calculation, and proposal ranking. The developed decision support system is implemented as a web-based application using the Laravel framework and a MySQL database. The results show that the application of the MOORA method is able to produce a ranking of research grant proposals based on the specified criteria and weights. The system can assist LPPM UMKT in managing the research grant selection process in a more structured and data-based manner, and can be used as a supporting tool for decision-making in research grant selection at higher education institutions.