Analysis of Student Satisfaction with Academic Services Based on Business Intelligence Information Systems

Abstract

This study presents a case study on the development of a Business Intelligence (BI) information system to analyze student satisfaction with academic services in a faculty in Indonesia. Measuring instruments adapt SERVQUAL (tangibles, reliability, responsiveness, assurance, empathy) and Net Promoter Score (NPS) to capture student loyalty. Synthetic survey data of 512 respondents (Likert scale 1–5) was used to demonstrate the methodology: extraction–transformation–loading (ETL) from the Academic Information System (AIS) into a data warehouse, star schema design, and dashboard visualization using Power BI. Reliability testing showed α=0.91; multiple linear regression analysis indicated responsiveness (β=0.34; p<0.001) and reliability (β=0.28; p<0.001) as the main predictors of satisfaction, while tangibles were not significant. The NPS of +21 signaled students’ inclination to promote the institution. These results are consistent with literature findings related to service quality improvement in higher education. This paper provides a replicable technical workflow and reporting template for similar contexts.