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Based on several studies that examine the K-Means Clustering method, it was found that in K-Means Clustering one of the weaknesses lies in the process of determining the center point of the cluster which also has implications for distance calculations in determining the similarity between data to obtain conclusions from the data. a cluster. And this is also caused by the influence of the percentage of the attributes used. If the attributes used are less relevant to their level of influence anddoi:10.30865/mib.v6i1.3366 fatcat:qmq3g6ec4je6foelail3yblyl4