Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Engineering Applied Science 2024 (ICoSTAS-EAS 2024)

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Implementation of the Convolutional Neural Network (CNN) Method for Sentiment Analysis in Teaching and Learning Process Evaluation (PBM)

Authors
I Wayan Suasnawa1, *, I Gusti Ngurah Bagus Catur Bawa1, Anak Agung Ngurah Gde Sapteka2, Ni Gusti Ayu Putu Harry Saptarini1, Ida Bagus Putra Manuaba1, I Komang Wiratama1
1Information Technology Department, Politeknik Negeri Bali, Bali, Indonesia
2Electrical Engineering Department, Politeknik Negeri Bali, Bali, Indonesia
*Corresponding author. Email: suasnawa@pnb.ac.id
Corresponding Author
I Wayan Suasnawa
Available Online 1 December 2024.
DOI
10.2991/978-94-6463-587-4_9How to use a DOI?
Keywords
Convolutional Neural Network (CNN); Learning Process; PBM
Abstract

This research aims to apply the Convolutional Neural Network (CNN) method in analyzing sentiment related to the teaching and learning process (PBM). PBM is a critical aspect in the world of education, and evaluation of this process can provide valuable insight for decision making. The CNN method is used to process text data containing PBM evaluations from student surveys. The steps in this research include data collection, data preprocessing, text representation, CNN architecture, training model, and evaluation model. It is hoped that the results of this research will provide insight into sentiment regarding PBM so that educational institutions can take appropriate action to improve the quality of the teaching and learning process. The CNN algorithm obtained an overall accuracy value of 72% with average negative, neutral, and positive precision values of 93%, 53%, and 83% respectively. This shows the ability to analyze sentiment is still lacking in neutral sentiment analysis.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Engineering Applied Science 2024 (ICoSTAS-EAS 2024)
Series
Advances in Engineering Research
Publication Date
1 December 2024
ISBN
978-94-6463-587-4
ISSN
2352-5401
DOI
10.2991/978-94-6463-587-4_9How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - I Wayan Suasnawa
AU  - I Gusti Ngurah Bagus Catur Bawa
AU  - Anak Agung Ngurah Gde Sapteka
AU  - Ni Gusti Ayu Putu Harry Saptarini
AU  - Ida Bagus Putra Manuaba
AU  - I Komang Wiratama
PY  - 2024
DA  - 2024/12/01
TI  - Implementation of the Convolutional Neural Network (CNN) Method for Sentiment Analysis in Teaching and Learning Process Evaluation (PBM)
BT  - Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Engineering Applied Science 2024 (ICoSTAS-EAS 2024)
PB  - Atlantis Press
SP  - 73
EP  - 79
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-587-4_9
DO  - 10.2991/978-94-6463-587-4_9
ID  - Suasnawa2024
ER  -