Cluster Analysis Application at the Five Largest Airports in Indonesia to Carry Out a Tax-Free Policy

摘要

The objective of this study is to apply cluster analysis on Indonesia's international tourism data set. Algorithm used in this cluster analysis is k-means and the number of cluster (k) is four and the similarity measurement between members of clusters is based on Euclidean distance. The source of data set was taken from Ministry of Tourism portal of Republic of Indonesia per November 2017. The results of this cluster analysis is presented in a table consisting of four clusters and each cluster consists of its members. Cluster analysis in this study can be used more quickly and efficiently to identify countries which will be the promotional and campaign targets on tax-free incentives for foreign tourists assuming a constraint that promotional and campaign budgets are always limited so that the related policy makers need to set a priority on targeted countries.