Proceedings of the 2nd Borobudur International Symposium on Science and Technology (BIS-STE 2020)

The Optimization of Neural Network Based PSO Feature Selection in the Classification of Graduates Working According to Their Field

Authors
Very Kurnia Bakti, Dairoh
Corresponding Author
Very Kurnia Bakti
Available Online 11 August 2021.
DOI
https://doi.org/10.2991/aer.k.210810.075How to use a DOI?
Keywords
College, neural network, PSO Feature Selection, Graduate
Abstract

The many college graduates who work not by their field of knowledge. Obtained show that the horizontal alignment of < 80% in the last three years has not reached the ideal value. The question that often arises is why this can happen and what influences can determine the quality result of graduates why they don’t work in their fields. we need a model that is used to see a pattern of graduates to work according to their scientific fields. In this research, the neural network algorithm method is used to see a pattern of graduates who work according to their scientific fields. The neural network is an algorithm method that can be used as a reliable classification algorithm but has shortcomings in its selection of features, wherewith the combination PSO has a good ability to solve problems that have non-linear and non-differentiable characteristics, multiple optima, large dimensions through good adaptations. derived from social psychological theory. We have obtained a higher accuracy of 71.51% using the combination of neural networks with PSO than that of one of the methods without PSO.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd Borobudur International Symposium on Science and Technology (BIS-STE 2020)
Series
Advances in Engineering Research
Publication Date
11 August 2021
ISBN
978-94-6239-416-2
ISSN
2352-5401
DOI
https://doi.org/10.2991/aer.k.210810.075How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Very Kurnia Bakti
AU  - Dairoh
PY  - 2021
DA  - 2021/08/11
TI  - The Optimization of Neural Network Based PSO Feature Selection in the Classification of Graduates Working According to Their Field
BT  - Proceedings of the 2nd Borobudur International Symposium on Science and Technology (BIS-STE 2020)
PB  - Atlantis Press
SP  - 434
EP  - 437
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.210810.075
DO  - https://doi.org/10.2991/aer.k.210810.075
ID  - Bakti2021
ER  -