Abstract
Cluster Analysis is a multivariate method in statistics. Agglomerative Hierarchical Cluster Analysis is one of approaches in Cluster Analysis. There are two linkage methods in Agglomerative Hierarchical Cluster Analysis which are Single Linkage and Complete Linkage. The purpose of this study is to compare between Single Linkage and Complete Linkage in Agglomerative Hierarchical Cluster Analysis. The comparison of performances between these linkage methods was shown by using Kruskal-Wallis test. The result of the comparison used for segmenting tourists of Kapas Island. The statistical software SPSS has been applied to analyze data of this research. The result from Kruskal-Wallis test shows Complete Linkage is more useful in identifying tourists segments. Keywords : Agglomerative Hierarchical Cluster Analysis, Single Linkage, Complete Linkage, Kruskal-Wallis test, tourists
Highlights
IntroductionSome methods have been developed to divide a sample of observations into some smaller groups
In statistics area, there are some methods available to gather observations
Single Linkage is a method that focused on minimum distances or nearest neighbor between clusters Complete Linkage concentrates on maximum distance or furthest neighbor between clusters
Summary
Some methods have been developed to divide a sample of observations into some smaller groups. One of the methods is Cluster Analysis This method involves sorting observations into different groups based on their similarity. Cluster Analysis refers as a collection of statistical methods that identifies groups of sample that show similar characteristics. There are many approaches in Cluster Analysis. One of the approaches is Agglomerative Hierarchical Cluster Analysis. The first step need to be considered in this approach is computation of similarity among cases or observation. The similarities among cases were considered as distance in Agglomerative Hierarchical Cluster Analysis. The cases that have same similarities will be set in the same clusters or groups. The distance among clusters can be compute using Single Linkage or Complete Linkage methods. Single Linkage is a method that focused on minimum distances or nearest neighbor between clusters Complete Linkage concentrates on maximum distance or furthest neighbor between clusters
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