Extended Fuzzy Topsis To Improve Prediction Student On Selection Properly Majors At Vocational School
| Main Author: | Nursikuwagus, Agus |
|---|---|
| Format: | TeachingResource PeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
http://repository.unikom.ac.id/67435/1/B_Jurnal_BA12_X.pdf http://repository.unikom.ac.id/67435/7/Similariti_Jurnal_BA12_Extended_Fuzzy_Topsis%20-%20Similarity.pdf http://repository.unikom.ac.id/67435/ http://kuliahonline.unikom.ac.id/?listmateri/&detail=44251 |
Daftar Isi:
- Kumpulan Penelitian This research aimed to predictability students on every test as a prerequisite to enter the major. Fuzzy Topsis, with the criteria and alternative approaches, can be determined according to the problems applied. The problem in fuzzy Topsis is not provided classification in the last step when we obtained many predictions classification. Fuzzy Topsis was executed only to get rank in a case. In order to solve that problem, we added a function in the last step fuzzy Topsis-like rule base. The rule base was divided into four majors, such as software engineering, animation, networking, and multimedia. To complete the prediction, we introduced some criteria that deployed some assessments, such as final examination, competency test, report, physical test, interview, and psychological tests. The results obtained for the process precision were 59.2%, and recall acquired 60%. The reason why the precision and recall were not got a high value because the dataset was very short (over fit), and only 270 to process in extended fuzzy Topsis. Another reason was the preference of function that was not proper for the dataset and imbalanced data, and dataset centered in one favorite major that was network and S/W engineering