# Segmenting the Higher Education Market: An Analysis of Admissions Data Using K-Means Clustering
> Prastyabudi W.A.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85193204374
Jurnal / Konferensi: Procedia Computer Science
Tahun terbit: 2024
DOI: https://doi.org/10.1016/j.procs.2024.02.156
ISSN: 18770509
Citations: 14

## Authors
- Prastyabudi W.A.

## Abstract
One of the affecting factors of marketing strategy in educational institutions is determining clear marketing objectives including suitable segmentation. This study develops a market segmentation for private HEIs considering the potential academic records of targeting schools and geographic factors. K-Means clustering method is exploited to cluster around 260 data with eight attributes. The elbow method and silhouette coefficient are used to determine the appropriate number of clusters. Findings suggest that schools within Cluster 1 and Cluster 4, with approximately 42% market share, are the primary market segment for deploying a robust and targeted marketing strategy.

## Keywords
- Computer science
- Market segmentation
- Cluster analysis
- Artificial intelligence
- k-means clustering
- Data mining
- Pattern recognition (psychology)
- Marketing
- Business

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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