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Application model of k-means clustering: Insights into promotion strategy of vocational high school

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dc.citedby33
dc.contributor.authorAbadi S.en_US
dc.contributor.authorMat The K.S.en_US
dc.contributor.authorNasir B.M.en_US
dc.contributor.authorHuda M.en_US
dc.contributor.authorIvanova N.L.en_US
dc.contributor.authorSari T.I.en_US
dc.contributor.authorMaseleno A.en_US
dc.contributor.authorSatria F.en_US
dc.contributor.authorMuslihudin M.en_US
dc.contributor.authorid57203514043en_US
dc.contributor.authorid57215912893en_US
dc.contributor.authorid55329377500en_US
dc.contributor.authorid56712456800en_US
dc.contributor.authorid57224709304en_US
dc.contributor.authorid57214479254en_US
dc.contributor.authorid55354910900en_US
dc.contributor.authorid57215910748en_US
dc.contributor.authorid57188749770en_US
dc.date.accessioned2023-05-29T06:53:36Z
dc.date.available2023-05-29T06:53:36Z
dc.date.issued2018
dc.description.abstractAdmission process is required in promoting the strategy to achieve the target. Through determining the strategic promotion, minimizing the cost in the marketing process could be reached with determining the appropriate promotion strategy. Data mining techniques in this initiative were applied to achieve in determining the promotional strategy. Using Clustering K-Means algorithm, it is one method of non-hierarchical clustering data in classifying student data into multiple clusters based on similarity of the data, so that student data that have the same characteristics are grouped in one cluster and that have different characteristics grouped in another cluster. Implementation using Weka Software is used to help find accurate values where the attributes include home address, school of origin, transportation, and reasons for choosing a school. The cluster of students was classified into five clusters in the following: the first cluster 22 students, the second cluster 10 students, the third cluster 10 students, the fourth cluster a total of 33 students, and the fifth cluster 25 students. The pattern of this result is supposed to contribute to enhance the significant data mining to support the strategic promotion in gaining new prospective students. � 2018 Satria Abadi et. al.en_US
dc.description.natureFinalen_US
dc.identifier.epage187
dc.identifier.issue2.27 Special Issue 27
dc.identifier.scopus2-s2.0-85067271003
dc.identifier.spage182
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85067271003&partnerID=40&md5=e0e7c8ae25a9896e72d4d49785c216b7
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23966
dc.identifier.volume7
dc.publisherScience Publishing Corporation Incen_US
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Technology(UAE)
dc.titleApplication model of k-means clustering: Insights into promotion strategy of vocational high schoolen_US
dc.typeArticleen_US
dspace.entity.typePublication
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