Proceedings of the 2nd International Conference on Vocational Education and Training (ICOVET 2018)

Preferences Analysis of Engineering Students on Choosing Learning Media using Support Vector Machine (SVM) Model

Authors
Aisyah Larasati, Apif Miftahul Hajji, Anik Nur Handayani
Corresponding Author
Aisyah Larasati
Available Online January 2019.
DOI
https://doi.org/10.2991/icovet-18.2019.15How to use a DOI?
Keywords
Preferences Analysis; Engineering Students; Learning Media, Artificial Neural Network
Abstract
This research aims to perform preferences analysis of engineering students on choosing learning media using Support Vector Machine (SVM) model. Data is collected using questionnaire. The questionnaire consists of four items related to students profile and 17 items related to students preferences on learning media. Respondents are students in Faculty of Engineering. The total number of usable respons are 1,911. Data were analyzed using Support Vector Machine Model and resulted in the accuracy of 98.48%. The results show that factors behind learning media choice and the using pattern of e-book as learning media are the most influence variables that affect engineering students preferences on choosing learning media.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2nd International Conference on Vocational Education and Training (ICOVET 2018)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
January 2019
ISBN
978-94-6252-668-6
ISSN
2352-5398
DOI
https://doi.org/10.2991/icovet-18.2019.15How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Aisyah Larasati
AU  - Apif Miftahul Hajji
AU  - Anik Nur Handayani
PY  - 2019/01
DA  - 2019/01
TI  - Preferences Analysis of Engineering Students on Choosing Learning Media using Support Vector Machine (SVM) Model
BT  - 2nd International Conference on Vocational Education and Training (ICOVET 2018)
PB  - Atlantis Press
SP  - 57
EP  - 59
SN  - 2352-5398
UR  - https://doi.org/10.2991/icovet-18.2019.15
DO  - https://doi.org/10.2991/icovet-18.2019.15
ID  - Larasati2019/01
ER  -