Application of K-Means In Grouping Tourist Visits To Bengkulu Province Tourist Attractions

Abstract

The management of attractions needs the support of Bengkulu Province Tourism Office, which is one of the government agencies in Bengkulu province. Every month a data collection on the number of visits to each tourist attraction in Bengkulu province will be carried out. From the large number of visit data that is calculated every year, Bengkulu provincial tourism office has difficulty in knowing the number of tourists and also difficulties in identifying which tourist objects are visited the most and least visited. The application for grouping tourist visits to tourist objects in Bengkulu province was made using the Visual Basic.net programming language and SQL Server 2008 data base by applying the Clustering Method, namely K-Means, the grouping was based on data on the number of tourist attraction visits for 12 months from January 2019 to with December 2019 which was divided into 4 attributes, namely Individual Adults (DP), Group Adults (DR), Individual Children (AP), and Group Children (AR). The data clustering process was carried out by dividing into 3 groups, namely Cluster 1 (high number of tourist visits), Cluster 2 (medium number of tourists) and cluster 3 (low number of tourists). Based on the results of the tests that have been carried out, the application for grouping tourist visits to tourist attractions in Bengkulu province has been successfully carried out, and can provide information based on 3 groups, namely Cluster C1 (high), Cluster C2 (medium) and Cluster C3 (low), as well as functionalities of the application. has worked as expected.