CLUSTER ANALYSIS ON SENIOR HIGH SCHOOLS OF KENDARI USING SIMILARITY WEIGHT AND FILTER METHODS

Abstract

In this paper, we aim to apply clustering method on senior high schools of Kendari using the
Similarity Weight and Filter Method (SWFM). This clustering method allows us to cluster
objects based on mixed variables, namely numerical and categorical variables. Before
implementing SWFM, we applied Wardhierarchical method on numerical variables and kmodes
on categorical variables. The results show that the schools can be grouped in 5 clusters.
Among these clusters, Cluster 1 is contained with state-owned and accredited highest rank
schools, while others are mostly private and accredited low rank schools.