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Fig. 7. Decision Tree of Web Application Course Grade Evaluation
Fig. 8. Performance of Decision Tree Model
classes the range of values is between A and AB. Meanwhile, ? label.
Class of 2017 gets a B and Class 2016 if the lecturer is VPW
then the grade is A and if the lecturer is ETO, then the grade As for the male, the activities carried out include, course
is B. For attendance below 96 % root decision making can be (loop? quiz ? course (loop) ? assignment ? course (loop)
seen completely in Figure 6 and Appendix II. ? forum ? URL ? file ? interactive content ? forum.
This is also in accordance with the results of the decision
Based on Figure 7, it can be grouped into students who tree, that gender is a variable that affects student graduation
pass and do not pass. Where grades A, AB, B, BC, C and D and assessment. Differences in lecturers do not have much
are students who pass lectures, while students with E grades influence, but have an impact on the delivery of the learning
are students who failed. Thus, if the assessment is grouped process in the classroom, so that a different path is obtained
into pass and fail, the result obtained is an accuracy of 100 %, for each lecturer.
because failed student is predicted as failed, and vice versa.
V. CONCLUSION CONFLICT OF INTEREST
Based on the result and discussion above, it can be con- The author have no conflict of relevant interest to this article.
cluded that each lecturer influences the flow of the learning
process in the classroom. There are also differences between REFERENCES
students who pass and do not pass in the learning path. In
general, there are differences between the paths carried out by [1] Q. Hu and H. Rangwala, “Towards fair educational data
female and male students. For female, the activities carried mining: A case study on detecting at-risk students,” in
out include course (loop) ? quiz ? course (loop) ? URL ? 13th International Conference on Educational Data Min-
file ? interactive content ? forum ? assignment ? course ing, pp. 431–437, 2020.
