<![CDATA[Students' end-of-semester grades show the results of the learning process that has been carried out for 1 semester, therefore accurate evaluation is very important to determine the extent to which learning objectives have been achieved properly. This research aims to create an appropriate prediction model to project students' final semester grades before the assessment period so that it can help teachers to identify at-risk students and provide appropriate treatment. This research uses the random forest algorithm and uses a dataset of student grades. The Random Forest model was successfully obtained through training and model evaluation using test data, showing an accuracy of 93.33%. The use of the random forest algorithm to predict students' final semester grades can be the right way to produce high accuracy for the benefit of educators in handling their students.]]>
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