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Penentuan Jumlah Kelas Matakuliah Menggunakan Fuzzy Tsukamoto dan Metode K-Means Cluster Yessy Fitriani; Mochamad Farid Rifai; M. Yoga Distra Sudirman
PETIR Vol 12 No 2 (2019): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.941 KB) | DOI: 10.33322/petir.v12i2.523

Abstract

The prediction of the number of courses is done by the department before making a schedule for each course. In practice, the number of classes in each course has a different number and there is often an opening or closing class when compiling a KRS due to the number of classes that are not in accordance with the number of students. A system is needed to produce a number of classes so that it can reduce the number of opening classes because the demand for a higher number of classes is in the class because of the interest in a class that will be opened. Fuzzy methods are used to predict students who will repeat the course based on student force and value variables. The K-Means method is used to classify the subjects with the number of students converted into 2 groups based on the number of students who have been taken and the number of students who repeat a number of subjects. The two methods used are implemented in the application system to predict the number of classes. The results of the fuzzy and K-method processes mean the output of the application predictions the number of classes.