Student Admission Promotion Strategy Mapping Using K-Means

Authors

  • Yanuar Wicaksono Universitas Alma Ata
  • Ujang Nendra Pratama Institut Seni Indonesia Yogyakarta
  • Siti Nurhasanah Universitas Alma Ata
  • Tri Utari Ramadania Universitas Alma Ata
  • Wulandari Juslan Universitas Alma Ata

DOI:

https://doi.org/10.29080/systemic.v7i1.1268

Keywords:

Promotion Strategy, Student Admission, K-Means

Abstract

Universities need to have a special strategy to capture the target prospective students. The variety of promotional media needs to be analyzed so that the media distribution is right on target. The number of new student admissions in each year of a college is influenced by the promotional actions that have been carried out. Data mining is a method for finding useful new information from a large amount of data collection and can help in making decisions. The analysis of promotion strategies grouped with the K-means algorithm is expected to be used by the promotion team in determining promotion strategies to get new prospective students in accordance with the promotion target. Promotional media that can be accessed in all provinces are the internet and leaflets/posters. For close-range media in promoting higher education, benefits can still be taken such as school visits, educational exhibitions, newspapers, billboards/banners. However, for provinces outside Yogyakarta, there are promotion strategies that can be relied upon, namely student recommendations and alumni recommendations

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References

Chaharsoughi, S. A. And Yasory, T. H. "Effect Of Sales Promotion On Consumer Behavior Based On Culture", vol.6, no.1, pp. 98–102. Doi: 10.5897/Ajbm11.739, 2012..

Cummins, Julian, and Roddy Mullin, "Sales promotion: How to create, implement and integrate campaigns that really work", Kogan Page Publishers, 2010.

Shimp, Terence A., "Periklanan Promosi (edisi kelima)", Jakarta: Erlangga, 2002.

Irawan, Y., & Wahyuni, R. “Sistem Pendukung Keputusan Penerimaan Siswa Baru di SMK Negeri 1 Tapung Hulu Menggunakan Metode Simple Multi Attribut Rating Technique (SMART)”, JOISIE (Journal Of Information Systems And Informatics Engineering), 3(1), 25. https://doi.org/10.35145/joisie.v3i1.405, 2019.

A. K. Jain, “Data clustering: 50 years beyond K-means,” Pattern Recognit. Lett., vol. 31, no. 8, pp. 651–666, 2010.

Anggreini, Novita Lestari, and Shandy Tresnawati, "Komparasi Algoritma K-Means dan K-Medoids untuk menangani Strategi Promosi di Politeknik TEDC Bandung." Jurnal TEDC, vol. 14, no. 2, pp. 120-127, 2020

Budiman, Ramdani, "Penerapan Data Mining Untuk Menentukan Lokasi Promosi Penerimaan Mahasiswa Baru Pada Universitas Banten Jaya (Metode K-Means Clustering)." ProTekInfo (Pengembangan Riset dan Observasi Teknik Informatika), vol. 6, no. 1, pp. 6-14, 2019.

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Published

2021-11-24

How to Cite

Wicaksono, Y., Nendra Pratama, U., Nurhasanah, S., Utari Ramadania, T., & Juslan, W. (2021). Student Admission Promotion Strategy Mapping Using K-Means. Systemic: Information System and Informatics Journal, 7(1), 42–48. https://doi.org/10.29080/systemic.v7i1.1268

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Articles