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Cluster Analysis Application at the Five Largest Airports in Indonesia to Carry Out a Tax-Free Policy
Condrobimo A.R.a, Nindito H.a, Dian Sano A.V.a, Kosala R.a, Ranti B.b, Harso Supangkat S.c
a Computer Science Department, BINUS Graduated Program-Computer Science, Bina Nusantara University, Jakarta, 11480, Indonesia
b Faculty of Computer Science, Universitas Indonesia, Depok, 16424, Indonesia
c Sekolah Teknik Elektro Dan Informatika, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.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.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Euclidean distance,Indonesia,International tourisms,Number of clusters,Policy makers,Similarity measurements,tax-free,Tourism portal[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]cluster analysis,data mining,tax-free[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICTSS.2018.8549963[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]