Melola Discovery

← Melola Discovery

Open access Journal SINTA 1

Data Mining Methods: K-Means Clustering Algorithms

International Journal of Cyber and IT Service Management · Vol. 3 No. 1 (2023) · pp. 40–47

DOI
10.34306/ijcitsm.v3i1.122
ISSN
2808-554X, 2797-1325
Published
2023-03-29
Publisher
Pandawan Sejahtera Indonesia
Language
en
License
creativecommons.org/licenses/by/4.0/

Abstract

A data warehouse is a straightforward definition of a database. Data mining technology can be used to process mountains of data in databases to uncover new, fascinating, and useful information.Clustering is an approach to data gathering. As one technique for grouping data into clusters or groups, the K-Means Clustering Algorithm algorithm divides the data into those that share the cluster's traits and those that don't. data into groups, and data into groups, so that data into groups, and data into groups, so that data has the same traits is grouped in the same cluster. Other clusters are formed from data and clusters with distinct properties. additional categories. The knowledge/information gathered in the groups or clusters is helpful to policy consumers in the decision-making process.mact of making decisions.

Keywords

Collaboration network of the authors

33 authors · 85 co-authorship links · 13 across different organisations

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

  • Universiti Teknologi MARA
  • Asian Institute of Management
  • Suan Sunandha Rajabhat University
  • Lincoln University College
  • University of Malaya
  • Skyline University College
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nusrat AhmedAffiliation unknown2
Mugiyo HartonoAffiliation unknown2
Albert TanAsian Institute of Management1
Olivier P. RocheAsian Institute of Management1
Md. Uzir Hossain UzirLincoln University College1
Samsul Farid SamsuddinUniversity of Malaya1
Suharti IshakUniversiti Teknologi MARA1
Mohd Rizaimy ShaharudinUniversiti Teknologi MARA1
Wissawa AunyawongSuan Sunandha Rajabhat University1
Natpatsaya SetthachotsombutSuan Sunandha Rajabhat University1
Y. RamakrishnaSkyline University College1
Shariff HarunUniversiti Teknologi MARA1
Azimah DaudUniversiti Teknologi MARA1
Moez MarrouchiAffiliation unknown1
Agus RaharjoAffiliation unknown1
Martin SudarmonoAffiliation unknown1
Anugrah Wahyu NugraAffiliation unknown1
Moch Fahmi AbdulazizAffiliation unknown1
Rezkya Wahyu AuliaAffiliation unknown1
Untung RahardjaAffiliation unknown1
Nanda SeptianiAffiliation unknown1
Cicilia Sriliasta BangunAffiliation unknown1
Tessa HandraAffiliation unknown1
Moh. BurhanudinAffiliation unknown1
sulaiman MPdAffiliation unknown1
Ulil AzmiAffiliation unknown1
Hermawan Pamot RaharjoAffiliation unknown1
Harry PramonoAffiliation unknown1
Dwi Gansar Santi WijayantiAffiliation unknown1
Adi SAffiliation unknown1
Donny Wira Yudha KusumaAffiliation 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)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Data Mining Methods: K-Means Clustering Algorithms</dc:title>
	<dc:creator xml:lang="en">Annas, Mohammad </dc:creator>
	<dc:creator xml:lang="en">Wahab, Siti Norida </dc:creator>
	<dc:subject xml:lang="en">Data Mining</dc:subject>
	<dc:subject xml:lang="en">Clustering</dc:subject>
	<dc:subject xml:lang="en">K-Means Clustering Algorithm</dc:subject>
	<dc:description xml:lang="en">A data warehouse is a straightforward definition of a database. Data mining technology can be used to process mountains of data in databases to uncover new, fascinating, and useful information.Clustering is an approach to data gathering. As one technique for grouping data into clusters or groups, the K-Means Clustering Algorithm algorithm divides the data into those that share the cluster's traits and those that don't. data into groups, and data into groups, so that data into groups, and data into groups, so that data has the same traits is grouped in the same cluster. Other clusters are formed from data and clusters with distinct properties. additional categories. The knowledge/information gathered in the groups or clusters is helpful to policy consumers in the decision-making process.mact of making decisions.</dc:description>
	<dc:publisher xml:lang="en">Pandawan Sejahtera Indonesia</dc:publisher>
	<dc:date>2023-03-29</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/122</dc:identifier>
	<dc:identifier>10.34306/ijcitsm.v3i1.122</dc:identifier>
	<dc:source xml:lang="en">International Journal of Cyber and IT Service Management; Vol. 3 No. 1 (2023): April ; 40-47</dc:source>
	<dc:source>2808-554X</dc:source>
	<dc:source>2797-1325</dc:source>
	<dc:source>10.34306/ijcitsm.v3i1</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://iiast.iaic-publisher.org/ijcitsm/IJCITSM/article/view/122/51</dc:relation>
	<dc:relation>10.34306/ijcitsm.v3i1.122.g51</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2023 Mohammad Annas, Siti Norida Wahab</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0/</dc:rights>
</oai_dc:dc>