The Optimization of Neural Network Based PSO Feature Selection in the Classification of Graduates Working According to Their Field
- DOI
- 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/).
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 - 10.2991/aer.k.210810.075 ID - Bakti2021 ER -