This study was conducted to study K-Means Clustering in knowledge retrieval. The purpose of this study is to obtain the results of the analysis of the application of clustering with the K-Means algorithm in determining the number of tourist interests in each travel agent that cooperates with PT Pulau Bintang Emas in Batam. The data used to support marketing strategy decisions include gender, age and travel agent, promos which are analyzed using the K-Means Clustering Algorithm so that the right customer cluster is known for the promotional approach. The data will be processed using Rapidminer data processing software with the K-Means Clustering Algorithm and a value of K = 3 so that the data will produce three clusters. The total data that has been tested using Rapidminer software is 398 records with 3 clusters obtained, namely: Cluster 0 totaling 130 items, Cluster 1 totaling 111 items and Cluster 2 totaling 157 items . With a computing speed of 0.01 seconds.
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