ROC and COPRAS Methods in New Student Admissions Application (PPDB) MAN HUMBANG HASUNDUTAN - Tua, Anri Hafiz; Putri, Raissa Amanda (Indonesian Journal of Data Science, IoT, Machine Learning and Informatics, 2025)
The development of information and communication technology, especially in the education sector, has opened up opportunities to increase efficiency and transparency in various processes, including New Student Admissions (PPDB). MAN Humbang Hasundutan faces challenges in manually screening hundreds of prospective students every year, which often introduces bias and inaccuracies in the selection process. Therefore, this research aims to develop a web-based PPDB application with the integration of the Rank Order Centroid (ROC) method for weighting criteria and Complex Proportional Assessment (COPRAS) for ranking. The ROC method assigns weights to criteria based on their level of importance, while the COPRAS method determines the ranking by taking into account the level of significance and utility of alternatives. The implementation of this application enables the processing of prospective student data quickly and objectively, as well as increasing the fairness and transparency of the selection process. Based on the results of previous research, the COPRAS method with ROC weighting has proven to be effective in assisting decision making in various fields. The proposed PPDB application is expected to simplify the selection process at MAN Humbang Hasundutan while increasing the credibility of the educational institution.