Student Mining Using K-Means Clustering: A Basis for Improving Higher Education Marketing Strategies

Melanie Arpay

doi:10.5281/zenodo.8383341

Research Article

Student Mining Using K-Means Clustering: A Basis for Improving Higher Education Marketing Strategies

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Melanie Arpay

Psych Educ Multidisc J, 2023, 14 (1), 1-9, DOI: https://doi.org/10.5281/zenodo.8383341, ISSN 2822-4353

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Abstract

This study aims to enhance marketing strategies in higher education institutions by applying data mining techniques, specifically K-means clustering. The research focuses on Mindanao State University - Lanao del Norte Agricultural College (MSU-LNAC), a tertiary institution in Northern Mindanao, Philippines, with the objective of increasing enrollment. The study utilizes the K-means algorithm to group attributes into different clusters. The clustering analysis provides valuable insights into the characteristics and preferences of the surveyed student population. Based on the findings, recommendations are presented to guide targeted marketing efforts, such as geographic targeting, collaborations with senior high schools, financial assistance programs, and the development of marketing campaigns that emphasize the institution's strengths and advantages. By implementing these recommendations, MSU-LNAC can enhance its recruitment and marketing strategies to attract and retain students effectively.

Keywords Data mining philippines k-means clustering Higher Education Institutions marketing strategies

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1 author, 1 institution.

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Bibliographic Information

Melanie Arpay (2023). Student Mining Using K-Means Clustering: A Basis for Improving Higher Education Marketing Strategies, Psychology and Education: A Multidisciplinary Journal, 14(1): 1-9

Bibtex Citation


                        
            @article{melanie_arpay2023pemj,

                author       = {Melanie Arpay},

                title        = {Student Mining Using K-Means Clustering: A Basis for Improving Higher Education Marketing Strategies},

                journal      = {Psychology and Education: A Multidisciplinary Journal},

                year         = {2023},

                volume       = {14},

                number       = {1},

                pages        = {1-9},

                doi          = {10.5281/zenodo.8383341},

                url          = {https://scimatic.org/show_manuscript/2041}

              }

APA Citation

Arpay, M., (2023). Student Mining Using K-Means Clustering: A Basis for Improving Higher Education Marketing Strategies. Psychology and Education: A Multidisciplinary Journal, 14(1), 1-9. https://doi.org/10.5281/zenodo.8383341

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Student Mining Using K-Means Clustering: A Basis for Improving Higher Education Marketing Strategies

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