<![CDATA[K-Means Clustering is a non-hierarchical data clustering method that groups data in the form of one or more clusters/groups. The role of costs is very important and cannot be separated from the activities of a company. The GAP between operational costs and work unit business exceeds the breakdown costs, causing an increase in operational costs every year. Financing logistics needs can be done with this method because this method can select and group clusters to be made which are considered suitable for operational costs which have a number of different groupings. It also aims to optimize the use of costs and optimize company profits. In the first experiment using 3 centroid cluster centers obtained randomly. The 3 centroid centers used in financing the company's operations are office maintenance costs, machine maintenance costs, and stationery costs which are grouped in the 2020 and 2021 periods for each operational cost date. This grouping aims to increase operational cost efficiency and increase the company's profits more optimally.]]>
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