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Use of Data Warehouse and Data Mining for Academic Data: A Case Study at a National University

International Journal of Cyber and IT Service Management · Vol. 1 No. 2 (2021) · pp. 206–215

DOI
10.34306/ijcitsm.v1i2.55
ISSN
2808-554X, 2797-1325
Published
2021-10-31
Publisher
Pandawan Sejahtera Indonesia
Language
en
License
creativecommons.org/licenses/by/4.0/

Abstract

If an organisation has full, rapid, exact, and accurate information, it may perform better in terms of evaluation, planning, and decision-making. The essential information can be derived from operational data maintained in an integrated database by a university that already has an information system. This research looks at how to collect operational data into a data warehouse and then apply data mining techniques to analyse the data. This study yielded a comprehensive data warehouse with a web-based information reporting application. Furthermore, data mining techniques are used to analyse the data warehouse that has been created. The result of the application of data mining is the generation of characteristic patterns of students who take certain specialization programs.

Keywords

Collaboration network of the authors

26 authors · 53 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Halu Oleo
  • Universitas Kanjuruhan
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nuke Puji Lestari SantosoAffiliation unknown2
Marviola HardiniAffiliation unknown1
Husni Teja SukmanaAffiliation unknown1
Aditya MardiansyahAffiliation unknown1
Gunawan GunawanUniversitas Halu Oleo1
Leli LeliAffiliation unknown1
Efa Ayu NabilaAffiliation unknown1
Windy Yestina SariAffiliation unknown1
Syarief Nur HusinAffiliation unknown1
Amirsyah TambunanAffiliation unknown1
Sugeng SantosoUniversitas Kanjuruhan1
HenderiAffiliation unknown1
Riri SetiawatiAffiliation unknown1
Lista MeriaAffiliation unknown1
SaukaniAffiliation unknown1
Desy PrastyaniAffiliation unknown1
Sudaryono SudaryonoAffiliation unknown1
Lusyani SunaryaAffiliation unknown1
Al HusainAffiliation unknown1
M Budi DjatmikoAffiliation unknown1
Leli NirmalasariAffiliation unknown1
Tatik MariyantiAffiliation unknown1
Muhammad Hakimi Mohd ShafiaiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://iiast.iaic-publisher.org/ijcitsm/index.php/IJCITSM/oai, first harvested 6 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Use of Data Warehouse and Data Mining for Academic Data : A Case Study at a National University</dc:title>
	<dc:creator xml:lang="en">Edastama, Primasatria</dc:creator>
	<dc:creator xml:lang="en">Dudhat, Amitkumar</dc:creator>
	<dc:creator xml:lang="en">Maulani, Giandari</dc:creator>
	<dc:subject xml:lang="en">Data Warehouse, Data Mining, Academic Data.</dc:subject>
	<dc:description xml:lang="en">If an organisation has full, rapid, exact, and accurate information, it may perform better in terms of evaluation, planning, and decision-making. The essential information can be derived from operational data maintained in an integrated database by a university that already has an information system. This research looks at how to collect operational data into a data warehouse and then apply data mining techniques to analyse the data. This study yielded a comprehensive data warehouse with a web-based information reporting application. Furthermore, data mining techniques are used to analyse the data warehouse that has been created. The result of the application of data mining is the generation of characteristic patterns of students who take certain specialization programs.</dc:description>
	<dc:publisher xml:lang="en">Pandawan Sejahtera Indonesia</dc:publisher>
	<dc:date>2021-10-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://iiast.iaic-publisher.org/ijcitsm/IJCITSM/article/view/55</dc:identifier>
	<dc:identifier>10.34306/ijcitsm.v1i2.55</dc:identifier>
	<dc:source xml:lang="en">International Journal of Cyber and IT Service Management; Vol. 1 No. 2 (2021): October; 206-215</dc:source>
	<dc:source>2808-554X</dc:source>
	<dc:source>2797-1325</dc:source>
	<dc:source>10.34306/ijcitsm.v1i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://iiast.iaic-publisher.org/ijcitsm/IJCITSM/article/view/55/18</dc:relation>
	<dc:relation>10.34306/ijcitsm.v1i2.55.g18</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2021 Primasatria Edastama, Amitkumar Dudhat, Giandari Maulani.</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0/</dc:rights>
</oai_dc:dc>