Penentuan Jumlah Kelas Matakuliah Menggunakan Fuzzy Tsukamoto dan Metode K-Means Cluster
Author(s) -
Yessy Fitriani,
Mochamad Farid Rifai,
M. Yoga Distra Sudirman
Publication year - 2019
Publication title -
petir
Language(s) - English
Resource type - Journals
eISSN - 2655-5018
pISSN - 1978-9262
DOI - 10.33322/petir.v12i2.523
Subject(s) - class (philosophy) , closing (real estate) , fuzzy number , fuzzy logic , mathematics , computer science , schedule , statistics , mathematics education , arithmetic , artificial intelligence , fuzzy set , political science , law , operating system
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.
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