Optimizing New Student Admissions

Overcoming Challenges with Business Intelligence to Achieve Efficiency and Quality of Decision Making

Abstract

This study aims to analyze the role of Business Intelligence (BI) in improving the efficiency and quality of decisions in the New Student Admission (PMB) process. The objectives of the research include an in-depth understanding of the operational challenges faced by educational institutions, as well as efforts to utilize BI to optimize PMB data management. The research method involves the implementation of BI in the process of collecting and analyzing PMB data. Predictive analytics are used to predict the academic performance of prospective students, allowing for smarter selection. The results of the study show that BI can improve operational efficiency by accelerating the selection process and providing a more solid basis for decision-making. This study underscores the importance of implementing BI in improving the quality of decision-making at the PMB level. The implementation of this technology not only helps the institution improve operational efficiency, but also provides a competitive advantage through a better understanding of the profile of prospective students.