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

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

Author

Listed:
  • Sahra Bilqis Fauziyyah

    (Telkom University)

  • Muhardi Saputra

    (Telkom University)

  • Riska Yanu Fa’rifah

    (Telkom University)

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.

Suggested Citation

  • Sahra Bilqis Fauziyyah & Muhardi Saputra & Riska Yanu Fa’rifah, 2023. "Analyzing Technostress Factors: Aspect-Based Sentiment Analysis for Identifying Causes in Fintech Users Using the Decision Tree Algorithm," Advances in Economics, Business and Management Research, in: Mahmud Dwi Sulistiyo & Ryan Adhitya Nugraha (ed.), Proceedings of the International Conference on Enterprise and Industrial Systems (ICOEINS 2023), pages 98-106, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-340-5_9
    DOI: 10.2991/978-94-6463-340-5_9
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