<![CDATA[Abstract: Vehicle maintenance is a very important sector in terms of economy and safety, a good understanding of vehicle maintenance is very important from the owner of the vehicle it self or from the company. Maintenance for the vehicle is considered as part structure of the activity in a series of improvements, as well as a planned activity to prevent potential errors resulting in damage. Schedule preventive maintenance is one of the methods that are used for vehicle maintenance scheduling. SPM is widely used because it can determine component reliability item, so as to reduce the cost of repairs, but this method has the disadvantage that reparations are made to the unit item could potentially breakdown, as well as the application of SPM only on certain types of vehicles. To solve this problem it is proposed the one application of a method, algorithm K-Means Clustering is one of the methods to be applied in the schedule vehicle maintenance services, K-Means algorithm is widely used because it is easy and simple. From the models created will then be tested using Confucion Matrix to determine how the level of accuracy, and describes the results of a positive predictive accuracy results are correct, the positive predictions were wrong, negative predictions are true, and false negative predictions. From these experiments showed that the application of K-Means Clustering algorithms in the vehicle's maintenance schedule capable of generating predictive value and accuracy that is optimal by 70%.]]>
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