The Effect of Professional Training, Computer Self-Efficacy, and Technology Acceptance Model on Digital Fraud Detection with Audit Digitalization as A Moderating Variable

Betri Betri (), S. M. Gumulya, Najmi Najmi and Lana Lutviyah
Additional contact information
Betri Betri: Universitas Muhammadiyah Palembang
S. M. Gumulya: Universitas Muhammadiyah Palembang
Najmi Najmi: Universitas Muhammadiyah Palembang
Lana Lutviyah: Universitas Muhammadiyah Palembang

A chapter in Proceedings of the 3rd International Conference on Management and Business (ICOMB 2024), 2025, pp 155-163 from Springer

Abstract: Abstract This research examines the influence of professional training, computer self-efficacy, and technology acceptance model on digital fraud detection with audit digitalization as a moderation variable. Sampling was done using saturated sampling to select the respondents. The respondents in this research were 79 internal Auditors at a conventional state-owned bank in Sumatra Selatan—method analysis using regression analysis. The F-test result shows that professional training, computer self-efficacy, and technology acceptance models significantly affect digital fraud detection. T-test results show that professional training does not substantially affect digital fraud detection. In contrast, computer self-efficacy and technology acceptance models have a significant effect on digital fraud detection partially. MRA test results, audit digitalization, is a predictor moderation for the influence of professional training, computer self-efficacy, and technology acceptance model on digital fraud detection.

Keywords: professional training; computer self-efficacy; technology acceptance model; digital fraud detection; audit digitalization (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-698-7_17

Ordering information: This item can be ordered from
http://www.springer.com/9789464636987

DOI: 10.2991/978-94-6463-698-7_17

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().