Proceedings of the International Conference on Enterprise and Industrial Systems (ICOEINS 2023)

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Analyzing Technostress Factors: Aspect-Based Sentiment Analysis for Identifying Causes in Fintech Users Using the Decision Tree Algorithm

Authors
Sahra Bilqis Fauziyyah1, *, Muhardi Saputra2, Riska Yanu Fa’rifah3
1Telkom University, Jl. Telekomunikasi, 40257, Bandung, Indonesia
2Telkom University, Jl. Telekomunikasi, 40257, Bandung, Indonesia
3Telkom University, Jl. Telekomunikasi, 40257, Bandung, Indonesia
*Corresponding author. Email: sahrabifa@student.telkomuniversity.ac.id
Corresponding Author
Sahra Bilqis Fauziyyah
Available Online 30 December 2023.
DOI
10.2991/978-94-6463-340-5_9How to use a DOI?
Keywords
Fintech; E-Wallet; Technostress; Aspect-Based Sentiment Analysis; LDA; Decision Tree C4.5
Abstract

Information technology innovation, particularly in Financial Technology (fintech), plays a central role in various aspects of life. Among the fintech services, e-wallets are highly popular in Indonesia. In 2021, OVO was a leading e-wallet; however, in 2022, it experienced a decline, suspected to be caused by technostress. People who experience technostress have negative attitudes and feelings towards technology. This research employs Aspect-Based Sentiment Analysis, using LDA topic modeling to identify four aspects: features, access, service, and security. OVO user reviews from Google Play Store were scraped for data analysis. Sentiment classification using C4.5 Decision Tree with a 75:25 data sharing ratio achieved high accuracies: features (96.79%), access (94.95%), service (92.19%), and security (96.36%). The results aid fintech companies, especially OVO, in addressing user technostress and enhancing user experience and engagement.

Copyright
© 2023 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 Enterprise and Industrial Systems (ICOEINS 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
30 December 2023
ISBN
10.2991/978-94-6463-340-5_9
ISSN
2352-5428
DOI
10.2991/978-94-6463-340-5_9How to use a DOI?
Copyright
© 2023 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  - Sahra Bilqis Fauziyyah
AU  - Muhardi Saputra
AU  - Riska Yanu Fa’rifah
PY  - 2023
DA  - 2023/12/30
TI  - Analyzing Technostress Factors: Aspect-Based Sentiment Analysis for Identifying Causes in Fintech Users Using the Decision Tree Algorithm
BT  - Proceedings of the International Conference on Enterprise and Industrial Systems (ICOEINS 2023)
PB  - Atlantis Press
SP  - 98
EP  - 106
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-340-5_9
DO  - 10.2991/978-94-6463-340-5_9
ID  - Fauziyyah2023
ER  -