APPLICATION OF K-MEANS ALGORITHM IN GROUPING OF CITY TOURISM CITY PAGAR ALAM

Abstract

The purpose of this study was to analyze the application of the k-means algorithm in classifying tourist visits to the city of Pagar Alam. The k-means algorithm in grouping tourist objects begins by determining the number of clusters to be formed, determining the centroid value of each cluster, calculating the distance between the data, and calculating the minimum object distance calculated. There are 10 tourism objects that are superior from the data from the Tourism Office of the City of Pagar Alam. The research data used is the number of tourist visitors during the COVID-19 pandemic, namely 2020. The data are grouped into 4 clusters, namely C1 = high number of tourist visitors, C2 = moderate number of tourist visitors, C3 = low number of tourist visitors, C4 = number of visitors travel is very low. the centroid values ​​used are C1 = 92,494, Centroid C2 = 71,658, Centroid C3 = 26,981 and centroid C4 = 4,485. then we get the results of grouping C1=Green Paradise tourism, C2=Janang Orange Gardens,, C3=Curup Tujuh Kenangan, Curup Mangkok, Curup dew, Tegur Wangi Site, Pelang Kenidai Village, and C4= Lumai Site, Tebing Tinggi Site and Tanjung Aro Site . From the results of grouping for c4 it becomes a note for the government of the City of Pagar Alam in increasing the number of tourist visitors.

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