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

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I whakaputaina i:TELKOMNIKA vol. 23, no. 4 (Aug 2025), p. 954-965
Kaituhi matua: Hidayat, Miwan Kurniawan
Ētahi atu kaituhi: Sugiarto, Dedy, Fitriana, Rina, Liang, Yun-Chia
I whakaputaina:
Ahmad Dahlan University
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024 7 |a 10.12928/TELKOMNIKA.v2314.26221  |2 doi 
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045 2 |b d20250801  |b d20250831 
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100 1 |a Hidayat, Miwan Kurniawan  |u Study Program of Industrial Engineering, Faculty of Engineering and Informatics, Universitas Bina Sarana Informatika, Jakarta, Indonesia 
245 1 |a Business intelligence system model to measure the performance of lecturers' scientific publications 
260 |b Ahmad Dahlan University  |c Aug 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Higher education 
653 |a Management decisions 
653 |a Data visualization 
653 |a Data mining 
653 |a Customer relationship management 
653 |a Executive information systems 
653 |a Clustering 
653 |a Performance evaluation 
653 |a Dimensional analysis 
653 |a Online analytical processing 
653 |a Hirsch index 
653 |a Intelligence (information) 
653 |a Design analysis 
653 |a Data analysis 
653 |a Machine learning 
653 |a Research methodology 
653 |a Bibliometrics 
653 |a Publications 
653 |a Business intelligence 
653 |a Decision making 
653 |a Prototyping 
653 |a Knowledge management 
653 |a Algorithms 
653 |a Performance management 
653 |a Data warehouses 
700 1 |a Sugiarto, Dedy  |u Master of Industrial Engineering, Faculty of Industrial Technology, Universitas Trisakti, Jakarta, Indonesia 
700 1 |a Fitriana, Rina  |u Master of Industrial Engineering, Faculty of Industrial Technology, Universitas Trisakti, Jakarta, Indonesia 
700 1 |a Liang, Yun-Chia  |u Department of Industrial Engineering and Management, College of Engineering, Yuan Ze University, Taoyuan City, Taiwan 
773 0 |t TELKOMNIKA  |g vol. 23, no. 4 (Aug 2025), p. 954-965 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3241349823/abstract/embedded/J7RWLIQ9I3C9JK51?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3241349823/fulltext/embedded/J7RWLIQ9I3C9JK51?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3241349823/fulltextPDF/embedded/J7RWLIQ9I3C9JK51?source=fedsrch