TELKOMNIKA Telecommunication, Computing, Electronics and Control
Hybrid clustering based on multi-criteria segmentation for higher education marketing

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Hybrid clustering based on multi-criteria segmentation for higher education marketing

Hybrid clustering
Multi-criteria segmentation
K-means
Self organizing map
Market segmentation

Market segmentation in higher education institutions is still rarely applied
although it can assist in defining the right strategies and actions for the
targeted market. The problem that often arises in market segmentation is how
to exploit the preferences of students as customers. To overcome this, the
combination of hybrid clustering method with multiple criteria will be
applied to the case of the market segmentation for students in higher
education institutions. The integration of geographic, demographic,
psychographic, and behavioral criteria from students is used to get more
insightful information about student preference. Data result of the integration
will be processed using hybrid clustering using K-means and self organizing
map (SOM) algorithm. The hybrid clustering conducted to get promising
clustering result along with the visualization of segmentation. This study

successfully produces five student segments. It received 1,386 as the Davies-
Bouldin index (DBI) value and 2,752 as the quantization error (QE) value

which indicates a good clustering result for market segmentation. In addition,
the visualization of the clustering result can be seen in a hexagonal map.

Hardika Khusnuliawati, Dhian Riskiana Putri

http://journal.uad.ac.id/index.php/TELKOMNIKA

Apr 22, 2021

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