This research aims to determine the probability of changes in grades from the prerequisite course Mathematical Statistics II using the Markov chain process method. Prerequisite courses are an important component in the higher education curriculum, because they influence student success in advanced courses. In this study, student grade data was collected and analyzed to map the transition between grade categories from one semester to the next. The Markov chain model is applied to predict patterns of value change, with the assumption that the future state of value depends only on the current state. It is hoped that the results of this research will provide insight into the pattern of grade transition, assist in academic decision making, and identify factors that contribute to an increase or decrease in student performance. Thus, this study can contribute to improving learning strategies and more effective academic policies.
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