Segmentation : As an Effort to Optimize the Number of New Student applicants at Private Universities
Segmentation : As an Effort to Optimize the Number of New Student applicants at Private Universities
Keywords:
Segmentation, Higher Education Institution, Marketing Communication Strategy, K-means
Abstract
The purpose a this study is to cluster (segment) users of higher education services at FE-USM to develop effective communication so as to increase the number of users of higher education services.The research method used was descriptive research, using convenience sampling with a sample size of 373 respondents from a population of 5,589. Data collection was conducted using a survey via Google Forms, and data processing was performed using the K-Means clustering method with SPSS.This study resulted in three clusters with the following membership: cluster 1 with 11 members, cluster 2 with 259 members, and cluster 3 with 3 members, where the cluster-forming variables were influenced by six variables, initially using eight variables. The six (6) variables that formed the clusters were age, occupation, marital status, income, reasons for choosing a university, and reasons for choosing a study program. The communication media that need to be developed are word of mouth, websites and social media, as well as brochures and banners with content tailored to each cluster.References
Angulo, F., Pergelova, A., & Rialp, J. (2010). A market segmentation approach for higher education based on rational and emotional factors. Journal of Marketing for Higher Education, 20(1), 1–17. https://doi.org/10.1080/08841241003788029
Budiman, R., Wiradharma, G., Harsasi, M., Riana, K. E., & Riady, Y. (2023). The potential of promotional media as a marketing instrument for open and distance higher education: a segmentation study. JMKSP (Jurnal Manajemen, Kepemimpinan, Dan Supervisi Pendidikan), 8(1), 515–528.
Davari, M., Noursalehi, P., & Keramati, A. (2019). Data mining approach to professional education market segmentation: A case study. Journal of Marketing for Higher Education, 29(1), 45–66.
Gazdecki Michałand Goryńska-Goldmann, E., Kiss, M., & Szakály, Z. (2021). Segmentation of food consumers based on their sustainable attitude. Energies, 14(11), 3179.
Hajibaba, H., Grün, B., & Dolnicar, S. (2020). Improving the stability of market segmentation analysis. International Journal of Contemporary Hospitality Management, 32(4), 1393–1411.
Khusnuliawati, H., & Putri, D. R. (2021). Hybrid clustering based on multi-criteria segmentation for higher education marketing. TELKOMNIKA (Telecommunication Computing Electronics and Control), 19(5), 1498–1506.
Kotler, P. (2012). Marketing Management/Philip Kotler, Kevin Lane Keller.-. Marketing, 1009, 4Ps.
Lozano, F. A. M., Cruz Pulido, J. M., & García Rodríguez, J. F. (2021). The market segmentation of higher education in Colombia reveals social inequalities. Cogent Education, 8(1). https://doi.org/10.1080/2331186X.2021.1877885
Miguéis, V. L., Freitas, A., Garcia, P. J. V, & Silva, A. (2018). Early segmentation of students according to their academic performance: A predictive modelling approach. Decision Support Systems, 115, 36–51.
Prastyabudi, W. A., Alifah, A. N., & Nurdin, A. (2024). Segmenting the Higher Education Market: An Analysis of Admissions Data Using K-Means Clustering. Procedia Computer Science, 234(2023), 96–105. https://doi.org/10.1016/j.procs.2024.02.156
Rahiminia, M., Razmi, J., Shahrabi Farahani, S., & Sabbaghnia, A. (2023). Cluster-based supplier segmentation: a sustainable data-driven approach. Modern Supply Chain Research and Applications, 5(3), 209–228.
Soto, J. J., Cantillo, V., & Arellana, J. (2021). Market segmentation for incentivising sustainable transport policies. Transportation Research Part D: Transport and Environment, 99, 103013.
Susilo, W. H. (2016). An Impact of Behavioral Segmentation to Increase Consumer Loyalty: Empirical Study in Higher Education of Postgraduate Institutions at Jakarta. Procedia - Social and Behavioral Sciences, 229, 183–195. https://doi.org/10.1016/j.sbspro.2016.07.128
Vázquez, J.-L., Lanero, A., Garc\’\ia, J. A., & Moraño, X. (2023). Segmentation of consumers based on awareness, attitudes and use of sustainability labels in the purchase of commonly used products. Sustainable Production and Consumption, 38, 115–129.
Wilkins, S. (2020). The positioning and competitive strategies of higher education institutions in the United Arab Emirates. International Journal of Educational Management, 34(1), 139–153.
Zhang, H. (2025). AI-driven innovation and entrepreneurship education: a K-means clustering approach for Chinese university students. Discover Artificial Intelligence, 5(1), 1–19.
Budiman, R., Wiradharma, G., Harsasi, M., Riana, K. E., & Riady, Y. (2023). The potential of promotional media as a marketing instrument for open and distance higher education: a segmentation study. JMKSP (Jurnal Manajemen, Kepemimpinan, Dan Supervisi Pendidikan), 8(1), 515–528.
Davari, M., Noursalehi, P., & Keramati, A. (2019). Data mining approach to professional education market segmentation: A case study. Journal of Marketing for Higher Education, 29(1), 45–66.
Gazdecki Michałand Goryńska-Goldmann, E., Kiss, M., & Szakály, Z. (2021). Segmentation of food consumers based on their sustainable attitude. Energies, 14(11), 3179.
Hajibaba, H., Grün, B., & Dolnicar, S. (2020). Improving the stability of market segmentation analysis. International Journal of Contemporary Hospitality Management, 32(4), 1393–1411.
Khusnuliawati, H., & Putri, D. R. (2021). Hybrid clustering based on multi-criteria segmentation for higher education marketing. TELKOMNIKA (Telecommunication Computing Electronics and Control), 19(5), 1498–1506.
Kotler, P. (2012). Marketing Management/Philip Kotler, Kevin Lane Keller.-. Marketing, 1009, 4Ps.
Lozano, F. A. M., Cruz Pulido, J. M., & García Rodríguez, J. F. (2021). The market segmentation of higher education in Colombia reveals social inequalities. Cogent Education, 8(1). https://doi.org/10.1080/2331186X.2021.1877885
Miguéis, V. L., Freitas, A., Garcia, P. J. V, & Silva, A. (2018). Early segmentation of students according to their academic performance: A predictive modelling approach. Decision Support Systems, 115, 36–51.
Prastyabudi, W. A., Alifah, A. N., & Nurdin, A. (2024). Segmenting the Higher Education Market: An Analysis of Admissions Data Using K-Means Clustering. Procedia Computer Science, 234(2023), 96–105. https://doi.org/10.1016/j.procs.2024.02.156
Rahiminia, M., Razmi, J., Shahrabi Farahani, S., & Sabbaghnia, A. (2023). Cluster-based supplier segmentation: a sustainable data-driven approach. Modern Supply Chain Research and Applications, 5(3), 209–228.
Soto, J. J., Cantillo, V., & Arellana, J. (2021). Market segmentation for incentivising sustainable transport policies. Transportation Research Part D: Transport and Environment, 99, 103013.
Susilo, W. H. (2016). An Impact of Behavioral Segmentation to Increase Consumer Loyalty: Empirical Study in Higher Education of Postgraduate Institutions at Jakarta. Procedia - Social and Behavioral Sciences, 229, 183–195. https://doi.org/10.1016/j.sbspro.2016.07.128
Vázquez, J.-L., Lanero, A., Garc\’\ia, J. A., & Moraño, X. (2023). Segmentation of consumers based on awareness, attitudes and use of sustainability labels in the purchase of commonly used products. Sustainable Production and Consumption, 38, 115–129.
Wilkins, S. (2020). The positioning and competitive strategies of higher education institutions in the United Arab Emirates. International Journal of Educational Management, 34(1), 139–153.
Zhang, H. (2025). AI-driven innovation and entrepreneurship education: a K-means clustering approach for Chinese university students. Discover Artificial Intelligence, 5(1), 1–19.
Published
2026-06-19
How to Cite
Wibisono, T., Kuswardani, D., Endang Yani, T., & Setiawan, W. (2026). Segmentation : As an Effort to Optimize the Number of New Student applicants at Private Universities. Kontigensi : Jurnal Ilmiah Manajemen, 14(1), 170-178. https://doi.org/10.56457/jimk.v14i1.920
Section
Articles
Copyright (c) 2026 Kontigensi : Jurnal Ilmiah Manajemen
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
By exercising the Licensed Rights, You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial 4.0 International Public License.