CUSTOMER GROUPING USING DYNAMIC CLUSTERS ON K-MEANS ALGORITHM TO DETERMINE FUTURE TOURIST PACKAGE

  • I Nyoman Yoga Setyawan Universitas Pendidikan Ganesha
  • Komang Drei Bayu Anggara Universitas Pendidikan Ganesha
  • I Putu Gde Karwina Styawan Universitas Pendidikan Ganesha
  • I Gede Wahyu Pramartha Universitas Pendidikan Ganesha
  • Gede Indrawan Universitas Pendidikan Ganesha
Keywords: Business Intelligence,Data Mining,K-Mean algorithm

Abstract

Business success highly dependent on utilization and the use of the data are used daily.
Data is able to provide insights into the future of business continuity and can be used as
reference for decision-making. Decision support based on the existing data is called the
Business Intelligence. Future travel packages required for the management revservasi in
determining product orders data travel packages using travel packages were sold on the
web-based online reservation system. K-Means algorithm is a clustering algorithm to
divide or partition the dataset into several clusters k, so it is easy to administer, relatively
quickly, easily adjusted as needed. Grouping customers using dynamic cluster on the K-
Means. There are three cluster with tourists information distribution with the country of
origin and the locations visited on each travel product package. Recommended future
travel package with products 2 Days / 1 Night Dive Safari for diving activities of
travelers to the management of the reservation system With the presence of this decision
support system, it is expected the travel packages determination become more targeted.

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Published
2017-12-11