OPTIMIZATION OF TOURISM STRATEGIES IN PAGAR ALAM CITY USING THE K-MEANS CLUSTERING ALGORITHM

Abstract

The aim of this research is to assist the Pagar Alam City Tourism Office in optimizing tourism strategies, especially cultural tourism. The large number of tours managed by the Pagar Alam City Tourism Office causes random data collection so that it is less complete in making the best decisions regarding tourism visit strategies and by optimizing tourism strategies to find out what strategies or steps are the highest based on the category and making it easier for the Tourism Office to make strategies. . This research uses the K-Means Clustering method as a calculation medium for strategy optimization. The development method used, namely CRIPS-DM, consists of six phases, namely the business understanding process, data understanding, data preparation, modeling, evaluation and deployment. The results obtained from this research produced 2 Clustering Patterns for the Number of Megalithic Tourist Visits in Pagaralam City with cluster_0 totaling 13 items with the highest number of visits, cluster_1 totaling 30 items with the lowest number of visits.