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Business intelligence system model to measure the performance of lecturers' scientific publications

Gorde:
Argitaratua izan da:TELKOMNIKA vol. 23, no. 4 (Aug 2025), p. 954-965
Egile nagusia: Hidayat, Miwan Kurniawan
Beste egile batzuk: Sugiarto, Dedy, Fitriana, Rina, Liang, Yun-Chia
Argitaratua:
Ahmad Dahlan University
Gaiak:
Higher education
Management decisions
Data visualization
Data mining
Customer relationship management
Executive information systems
Clustering
Performance evaluation
Dimensional analysis
Online analytical processing
Hirsch index
Intelligence (information)
Design analysis
Data analysis
Machine learning
Research methodology
Bibliometrics
Publications
Business intelligence
Decision making
Prototyping
Knowledge management
Algorithms
Performance management
Data warehouses
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Laburpena:Scientific publication data is sourced from the SINTA website to measure the performance of journals, institutions, and researchers in Indonesia. Accessing and analyzing data for institutional needs is restricted, and lecturer development patterns based on lecturer characteristics remain untapped. 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. 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 snowflake's schema, which has data of 368 KB and a processing time of 0.00611 seconds. Davies-Bouldin Index (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.
ISSN:1693-6930
2302-9293
DOI:10.12928/TELKOMNIKA.v2314.26221
Baliabidea:Advanced Technologies & Aerospace Database