M easurement of the performance of scientific publications at universities based on the number of published scientific papers plays a role in developing lecturers to improve the quality of education. Scientific publication data is sourced from the Sinta website to measure the performance of journals, institutions, and researchers in Indonesia. Still, access and analysis of data for internal institutional needs are limited, and information has not been utilized on lecturer development patterns that are by the characteristics of lecturers. The study aims to analyze and design business intelligence system models to measure the performance of scientific publications using dimensional models, clustering, On-Line Analytical Processing (OLAP), and prototyping. Research methods are carried out through data, and information needs analysis, data warehouse design, data mining and OLAP application, business intelligence system development, and system evaluation. This research produces a business intelligence system model to measure the performance of scientific publications using dimensional models by applying data mining and OLAP. The resulting dimensional models are the researcher index model, the researcher score model, the publication article model, and the research subject model. Measurements of data size and processing time show that the star schema has data of 336 KB and a processing time of 0.00554 seconds, is the best model compared to the snowflakes schema, which has data of 368 KB and a processing time of 0.00611 seconds. DBI measurements show the best clustering performance is the X-Means algorithm with K as many as 5 clusters (Kmin = 3, Kmax = 5) and a DBI value of 0.537040.