TATA KELOLA DATABASE PERGURUAN TINGGI YANG OPTIMAL DENGAN DATA WAREHOUSE
Abstract
The emergence of new higher education institutions has created the competition in higher education market, and data warehouse can be used as an effective technology tools for increasing competitiveness in the higher education market. Data warehouse produce reliable reports for the institution’s high-level management in short time for faster and better decision making, not only on increasing the admission number of students, but also on the possibility to find extraordinary, unconventional funds for the institution. Efficiency comparison was based on length and amount of processed records, total processed byte, amount of processed tables, time to run query and produced record on OLTP database and data warehouse. Efficiency percentages was measured by the formula for percentage increasing and the average efficiency percentage of 461.801,04% shows that using data warehouse is more powerful and efficient rather than using OLTP database. Data warehouse was modeled based on hypercube which is created by limited high demand reports which usually used by high level management. In every table of fact and dimension fields will be inserted which represent the loading constructive merge where the ETL (Extraction, Transformation and Loading) process is run based on the old and new files.
Full Text:
PDFReferences
. Silva FSC, Panigassi R, Hulot C. Learning Management Systems Desiderata for Competitive Universities. European Journal of Open Distance and E-Learning. 2007; 13(2): 121-129.
. Ward J, Peppard J. Strategic planning for Information Systems. Third Edition. West Susse: John Willey & Sons Ltd. 2003.
. Porter ME. Strategy and the Internet. Harvard Business Review. 2001; 79(3): 62-78.
. Dimokas N, Mittas N, Nanopoulos A, Angelis L. A Prototype System for Educational Data Warehousing and Mining. Proceedings of the 2008 Panhellenic Conference on Informatics. 2008: 199-203.
. Wikramanayake GN, Goonetillake JS. Managing Very Large Databases and Data Warehousing. Sri Lankan Journal of Librarianship and Information Management. 2006;2(1):22-29.
. Goldstein PJ, Karzt RN. Academic Analytics: The Uses of Management Information and Technology in Higher Education. EDUCAUSE Review. 2005; 7(1): 1-12.
. Hans D, Gomez JM, Peters D, Solsbach A. Case Study-Design for Higher Education-A Demonstration in the Data Warehouse Environment. in: Abramowicz W. Flejter D (Editors). BIS 2009 Workshop. LNBIP. 2009; 37: 231-241.
. Wu T. System of Teaching Quality Analyzing and Evaluating Based on Data Warehouse. Computer Engineering and Design. 2009; 30(6): 1545-1547.
. Zhou L, Wu M, Li S. Design of Data Warehouse in Teaching State Based on OLAP and Data Mining. Proc. SPIE (The International Society for Optical Engineering). 2009; 7344: 23-29.
. Gombiro C, Munyoka W, Hove S, Chengetanai G, Zano C. The Need for Data Warehousing in Sharing Learning Materials. Journal of Sustainable Development in Africa. 2008; 10(2): 422-449.
. Ranjan J, Khalil S. Conceptual Framework of Data Mining Process in Management Education in India: An Institutional Perspective. Information Technology Journal. 2008; 7(1): 16-23.
. Calero C, Piatiini M, Pascual C, Serrano MA. Towards Data Warehouse Quality Metrics. Proceedings of the 3rd Intl. Workshop on Design and Management of Data Warehouses (DMDW'2001). Interlaken. Switzerland. 2001; 39: 2-11.
DOI: http://doi.org/10.12928/telkomnika.v8i1.601
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120
Fax: +62 274 564604