Clustering Tourism Object in Bali Province Using K-Means and X-Means Clustering Algorithm
Stephanie Monica, Friska Natalia, Sud Sudirman · 2018
Tourism is an important element in Indonesian economy as it brings consistent flow of foreign currencies as well as supporting local industries. One way for the Indonesian government to improve this industry is to identify areas and localities which requires more attention and investment. This paper presents our finding from analysing the large amount of data that the Indonesian Government Tourism Office, specifically regarding tourism in Bali. We use K-Means and X-Means algorithms to cluster the various type of tourist attractions in Bali according to their popularity and Power BI to develop the interactive dashboard. The visualisation of the results is subsequently generated for non-technical persons to be able to understand. The output of this research should feed into the decision making process taken by the Bali Provincial Government in order to improve the number of visitors to the numerous tourist attractions spread throughout the region.