Algoritma Naive Bayes untuk Prediksi Keberhasilan Mahasiswa pada Mata Kuliah Praktikum
Keywords:
Success, Student, Practical courses, Naive Bayes, PredictionAbstract
The lecture system at BSI University has practicum courses, where the teaching and learning process is 20% theory and 80% practicum by learning software according to current technological developments. In the practicum-based teaching and learning process, there are several problems including understanding the content of the material delivered by the lecturer, communication between students in class and lecturers because there are many discussions, in practicum learning made in groups to make projects, this group cohesiveness is also an assessment in achieving predetermined targets, the learning atmosphere also supports the teaching and learning process, the process of lecturer assessment of students will be the final result of learning and teaching activities. In the practicum course, 4 credits are provided and this 4 credits time is still considered insufficient to complete quite a lot of material at each meeting, from these problems the author wants to know the prediction of student success rates in practicum course learning. This study uses the naive bayes method with a total sample of 130 samples from the results of a questionnaire distributed to students with 20 questions, so that this study results in that students feel successful in practicum course learning with an accuracy level of 100%, a precision level of 100%, and a recall level of 100% after being processed using rapidminer 5 software.References
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