<![CDATA[Delivery of finished goods is carried out based on the incoming PO from the customer and received by the Marketing Department. The Marketing Department will make a DO based on the PO that has been received and then the DO will be forwarded to the Shipping Section to make a Packing List. The packing list that has been made will be validated by the section head and the items contained in the packing list will be prepared by the Prepare Subsection. The validated packing list will be printed and forwarded to the Delivery Sub-section for delivery with the goods that are ready to be shipped. Shipping lines are made by the shipping coordinator based on the thoughts of the shipping coordinator, this causes the distance between one driver and another driver to be uneven. To overcome this problem, we need a method of dividing the task of delivering finished goods to customers. The method used is the K-Means Clustering Method. The K-Means Clustering method is a clustering method that partitions data into clusters so that data that have similarities are in the same cluster. In this study, the K-Means Clustering method was proven to be able to minimize the difference in distance between the driver and one PIC with the other driver and PIC. The difference in distance between the manual method and the K-Means Clustering method is 87,203 km.]]>
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