Application model of k-means clustering: Insights into promotion strategy of vocational high school
Admission 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 ach...
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my.uniten.dspace-239662023-05-29T14:53:36Z Application model of k-means clustering: Insights into promotion strategy of vocational high school Abadi S. Mat The K.S. Nasir B.M. Huda M. Ivanova N.L. Sari T.I. Maseleno A. Satria F. Muslihudin M. 57203514043 57215912893 55329377500 56712456800 57224709304 57214479254 55354910900 57215910748 57188749770 Admission 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. Final 2023-05-29T06:53:36Z 2023-05-29T06:53:36Z 2018 Article 2-s2.0-85067271003 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067271003&partnerID=40&md5=e0e7c8ae25a9896e72d4d49785c216b7 https://irepository.uniten.edu.my/handle/123456789/23966 7 2.27 Special Issue 27 182 187 Science Publishing Corporation Inc Scopus |
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Admission 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. |
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57203514043 |
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57203514043 Abadi S. Mat The K.S. Nasir B.M. Huda M. Ivanova N.L. Sari T.I. Maseleno A. Satria F. Muslihudin M. |
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Abadi S. Mat The K.S. Nasir B.M. Huda M. Ivanova N.L. Sari T.I. Maseleno A. Satria F. Muslihudin M. |
| spellingShingle |
Abadi S. Mat The K.S. Nasir B.M. Huda M. Ivanova N.L. Sari T.I. Maseleno A. Satria F. Muslihudin M. Application model of k-means clustering: Insights into promotion strategy of vocational high school |
| author_sort |
Abadi S. |
| title |
Application model of k-means clustering: Insights into promotion strategy of vocational high school |
| title_short |
Application model of k-means clustering: Insights into promotion strategy of vocational high school |
| title_full |
Application model of k-means clustering: Insights into promotion strategy of vocational high school |
| title_fullStr |
Application model of k-means clustering: Insights into promotion strategy of vocational high school |
| title_full_unstemmed |
Application model of k-means clustering: Insights into promotion strategy of vocational high school |
| title_sort |
application model of k-means clustering: insights into promotion strategy of vocational high school |
| publisher |
Science Publishing Corporation Inc |
| publishDate |
2023 |
| _version_ |
1806427507941965824 |
| score |
13.211869 |