Classification of Thesis Topics Based on Informatics Science Using SVM
| Autor: | Eka Mala Sari Rochman, Ach. Khozaimi, Devie Rosa Anamisa, Muhammad Ali Syakur, Ika Oktavia Suzanti, Aeri Rachmad, Imamah |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | IOP Conference Series: Materials Science and Engineering. 1125:012033 |
| ISSN: | 1757-899X 1757-8981 |
| DOI: | 10.1088/1757-899x/1125/1/012033 |
| Popis: | Thesis topic is an inseparable part in the world of tertiary education. Determining the thesis topic becomes a problem for students. The determination of the thesis topic leads to the trend of the topic in the development of computer science. The determination of the topic of thesis for students often ignores their ability to process. Ideally in determining the topic of the thesis, the record of student grades can be an important variable in deciding topics for students, where the student’s grade record is contained in the transcript. Therefore, this study uses the Support Vector Machine (SVM) method in recommending thesis topics by classifying selected subject groups that have been taken by students. The Support Vector Machine method is a classification method of supervision because it requires testing data and training data as a training process at the time of prediction. Support Vector Machine provides an optimal model, which provides a solution with a maximum margin to determine the distance of data to the hyperplane. The test results show an accuracy of 80%. |
| Databáze: | OpenAIRE |
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