<![CDATA[The objectives of this study are: (1) To get and provide the right periodic maintenance implementation time on CC201 locomotive maintenance. (2) To get and provide the right periodic maintenance implementation time on CC203 locomotive maintenance. The method used in this research is Markov Chain, using the type of applied research. This research uses a quantitative approach. The data collection techniques used are (1) Primary Data Collection; and (2) Secondary Data Collection. Meanwhile, the research instruments used (1) Observation Sheet; and (2) Documentation. The data analysis used is (1) Determination of Condition or State; (2) Creating a Transition Matrix; and (3) Steady State Analysis to get the probability of locomotive conditions in good condition, lightly damaged, moderately damaged or severely damaged. The results of this study show that: (1) The right periodic maintenance implementation time on CC201 locomotive maintenance is proposal II at interval P2 with the highest probability of good condition of 0.609 and the lowest probability of heavy condition of 0.021. With this, a maintenance scheduling policy is obtained for every 1 month to perform periodic maintenance on day 7,128. (2) The right periodic maintenance implementation time for CC203 locomotive maintenance is proposal II at interval P2 with the highest probability in good condition of 0.619 and the lowest probability in severe condition of 0.142. With this, a maintenance scheduling policy is obtained for every 1 month to perform periodic maintenance on day 24,516.]]>
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