Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering
One of the strategic plans of the developing universities in obtaining new students is forming a partnership with surrounding high schools. However, partnerships made does not always behave as expected. This paper presented the segmentation technique to the previous new student admission dataset usi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Diponegoro University
2020-04-01
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| Series: | Jurnal Teknologi dan Sistem Komputer |
| Subjects: | |
| Online Access: | https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13352 |
| _version_ | 1797285174779576320 |
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| author | Syahroni Hidayat Ria Rismayati Muhammad Tajuddin Ni Luh Putu Merawati |
| author_facet | Syahroni Hidayat Ria Rismayati Muhammad Tajuddin Ni Luh Putu Merawati |
| author_sort | Syahroni Hidayat |
| collection | DOAJ |
| description | One of the strategic plans of the developing universities in obtaining new students is forming a partnership with surrounding high schools. However, partnerships made does not always behave as expected. This paper presented the segmentation technique to the previous new student admission dataset using the integration of recency, frequency, and monetary (RFM) analysis and fuzzy c-means (FCM) algorithm to evaluate the loyalty of the entire school that has bound the partnership with the institution. The dataset is converted using the RFM approach before processed with the FCM algorithm. The result reveals that the schools can be segmented, respectively, as high potential (SP), potential (P), low potential (CP), and very low potential (KP) categories with PCI value 0.86. From the analysis of SP, P, and CP, only 71 % of 52 school partners categorized as loyal partners. |
| first_indexed | 2024-03-07T17:59:29Z |
| format | Article |
| id | doaj.art-29bfa00bfef7456388f55484cedb4cb8 |
| institution | Directory Open Access Journal |
| issn | 2338-0403 |
| language | English |
| last_indexed | 2024-03-07T17:59:29Z |
| publishDate | 2020-04-01 |
| publisher | Diponegoro University |
| record_format | Article |
| series | Jurnal Teknologi dan Sistem Komputer |
| spelling | doaj.art-29bfa00bfef7456388f55484cedb4cb82024-03-02T11:05:15ZengDiponegoro UniversityJurnal Teknologi dan Sistem Komputer2338-04032020-04-018213313910.14710/jtsiskom.8.2.2020.133-13912816Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clusteringSyahroni Hidayat0https://orcid.org/0000-0002-5034-0535Ria Rismayati1Muhammad Tajuddin2Ni Luh Putu Merawati3Department of Computer Science, Universitas Bumigora, IndonesiaDepartment of Computer Science, Universitas Bumigora, IndonesiaDepartment of Computer Science, Universitas Bumigora, IndonesiaDepartment of Computer Science, Universitas Bumigora, IndonesiaOne of the strategic plans of the developing universities in obtaining new students is forming a partnership with surrounding high schools. However, partnerships made does not always behave as expected. This paper presented the segmentation technique to the previous new student admission dataset using the integration of recency, frequency, and monetary (RFM) analysis and fuzzy c-means (FCM) algorithm to evaluate the loyalty of the entire school that has bound the partnership with the institution. The dataset is converted using the RFM approach before processed with the FCM algorithm. The result reveals that the schools can be segmented, respectively, as high potential (SP), potential (P), low potential (CP), and very low potential (KP) categories with PCI value 0.86. From the analysis of SP, P, and CP, only 71 % of 52 school partners categorized as loyal partners.https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13352new student recruitment strategyfuzzy c-meansrfm analysiscustomers loyalty |
| spellingShingle | Syahroni Hidayat Ria Rismayati Muhammad Tajuddin Ni Luh Putu Merawati Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering Jurnal Teknologi dan Sistem Komputer new student recruitment strategy fuzzy c-means rfm analysis customers loyalty |
| title | Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering |
| title_full | Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering |
| title_fullStr | Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering |
| title_full_unstemmed | Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering |
| title_short | Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering |
| title_sort | segmentation of university customers loyalty based on rfm analysis using fuzzy c means clustering |
| topic | new student recruitment strategy fuzzy c-means rfm analysis customers loyalty |
| url | https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13352 |
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