A Multi Criteria Decision Making to Support Major Selection of Senior High School
Author(s) -
Adhistya Erna Permanasari,
Marsetyo Wisaksono,
Sri Suning Kusumawardani
Publication year - 2020
Publication title -
ijitee (international journal of information technology and electrical engineering)
Language(s) - English
Resource type - Journals
ISSN - 2550-0554
DOI - 10.22146/ijitee.54427
Subject(s) - multiple criteria decision analysis , analytic hierarchy process , topsis , selection (genetic algorithm) , computer science , normalization (sociology) , management science , operations research , process (computing) , mathematics , machine learning , engineering , sociology , anthropology , operating system
Senior high school students need to select a specialization, such as Mathematics and Natural Sciences, Social Sciences, or Language and Culture. This selection process can be improved by using Multi Criteria Decision Making (MCDM) methods. When MCDM methods are implemented, AHP method has accuracy of 61%, whereas AHP-Fuzzy TOPSIS 1 and AHP-Fuzzy TOPSIS 2 have accuracy of 75%. This research implements tests and analyzes new MCDM method, which is Hybrid MCDM Model, in helping aforementioned specialization selection process. There are four basic steps in Hybrid MCDM Model: performing experimental design to obtain attributes' weight and criteria, evaluating MCDM with the three existing methods, performing RSM regression to derive mathematical model, and decision making. This research introduces data normalization to the mathematical model which results in better implementation of Hybrid MCDM Model in the senior high school students' specialization selection process. Hybrid MCDM Model in the senior high school student specialization selection has accuracy of 86%, which includes 11% accuracy improvements compared to other applied MCDM methods.
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