Pengaruh Persepsi Penggunaan Artificial Intelligence terhadap Kualitas Audit
Abstract
This study aims to examine the influence of the perception of artificial intelligence ease of use and the perception of artificial intelligence usefulness on audit quality. Quantitative causality is the term for this type of research. A closed questionnaire was used to collect research data, which was then distributed via linkedIn, email, and whatsApp. The sampling method used was non-probability sampling, specifically convenience sampling, with a total of 121 valid respondents who were external auditors from Public Accounting Firms (KAP) in Indonesia. Because the data was obtained from easily accessible respondents, there is potential for sample bias that could affect the representativeness and external validity of the research findings. Data analysis was performed using multiple linear regression with SPSS version 26. The research results indicate that the perception of artificial intelligence usefulness has a positive and significant impact on audit quality, while the perception of artificial intelligence ease of use has a negative and non-significant impact on audit quality.
References
Adeoye, I. O., Akintoye, R. I., Theophilus, A. A., & Olagunju, O. A. (2023). Artificial intelligence and audit quality: Implications for practicing accountants. Asian Economic and Financial Review, 13(11), 756–772. https://doi.org/10.55493/5002.v13i11.4861
Albawwat, I., & Frijat, Y. Al. (2021). An analysis of auditors’ perceptions towards artificial intelligence and its contribution to audit quality. Accounting, 7(4), 755–762. https://doi.org/10.5267/j.ac.2021.2.009
Al-Sayyed, S. M., Al-Aroud, S. F., & Zayed, L. M. (2021). The effect of artificial intelligence technologies on audit evidence. Accounting, 7(2), 281–288. https://doi.org/10.5267/j.ac.2020.12.003
Ardianingsih, A. (2021). Audit Laporan Keuangan. Bumi Aksara.
Bailey, D. R., Almusharraf, N., & Almusharraf, A. (2022). Video conferencing in the e-learning context: explaining learning outcome with the technology acceptance model. Education and Information Technologies, 27(6), 7679–7698. https://doi.org/10.1007/s10639-022-10949-1
BDO. (2024). BDO Survey Finds AI is Expected to Unlock More Efficient Audits, but Can’t Replace Human Element. Https://Www.Bdo.Com/Insights/Press-Releases/Bdo-Survey-Finds-Ai-Is-Expected-to-Unlock-More-Efficient-Audits-but-Can-t-Replace-Human-Element?Utm_source=chatgpt.Com.
Chuttur, M. (2009). Association for Information Systems AIS Electronic Library (AISeL) All Sprouts Content Sprouts Overview of the Technology Acceptance Model: Origins, Developments and Future Directions. http://aisel.aisnet.org/sprouts_all
Darmadi, D., & Rasyid, T. (2019). Analisis Kualitas Pemeriksaan Pengelolaan Keuangan Negara oleh Badan Pemeriksaan Keuangan Republik Indonesia Perwakilan Sulawesi Selatan. Jurnal Ilmu Administrasi, 3.
Darmawan Suwandi, E. (2021). Kualitas Audit Perusahaan Pada Masa Pandemic Covid 19 (Studi Literatur). In Jurnal Akuntansi Keuangan dan Bisnis (Vol. 14, Issue 1). https://jurnal.pcr.ac.id/index.php/jakb/
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
Deniz, A., & Jeffery, S. (2022). Artificial intelligence and the auditor: Are you ready? Retrieved from Https://Idea.Caseware.Com/Ai Auditor-Are-You-Ready/ .
Efferin, S., & Harindahyani, S. (2024). Akuntan dan Profesi Akuntansi di Era Artificial Intelligence. https://www.researchgate.net/publication/385887431
FRC. (2020). The Use Of Technology in The Audit Of Financial Statements AQR Thematic Review.
Halim, M., & Aspirandi, R. M. (2023). Peran Akuntansi Manajemen Strategik Terhadap Pengambilan Keputusan Bisnis Melalui Analisis Big Data dan Artificial Intelligence: Suatu Studi Literature Review. JIAI (Jurnal Ilmiah Akuntansi Indonesia), 8(1), 110–128. https://doi.org/10.32528/jiai.v8i1.11878
https://pppk.kemenkeu.go.id/in/post/daftar-kantor-akuntan-publik-aktif. (n.d.). “Daftar Kantor Akuntan Publik Aktif.” Accessed on Date March 21, 2025. .
IAASB. (2019). Overall Objectives of the Independent Auditor and the Conduct of an Audit in Accordance with International Standards on Auditing. International Standard on Auditing (ISA).
Isam Al-Qatamin, K., Salleh, Z., & Isam AL-Qatamin, K. (2020). Audit Quality: A Literature Overview and Research Synthesis. 22, 56–66. https://doi.org/10.9790/487X-2202025666
Issa, H., Sun, T., & Vasarhelyi, M. A. (2016). Research Ideas for Artificial Intelligence in Auditing: The Formalization of Audit and Workforce Supplementation. Journal of Emerging Technologies in Accounting, 13(2), 1–20. https://doi.org/10.2308/jeta-10511
Khudhair, D. Z., Babylon, U., Usama Alhayaly, A., Hamzh, E. M., Rubaie, A., Madhi, E., & Al Rubai, H. (2024). Al-Qadisiyah Journal for Administrative and Economic Sciences The Impact of Artificial Intelligence Techniques on External Audit Quality and Its Reflection on the Expectation Gap: An Exploratory Study from the Perspective of Auditors in Iraqi Audit Firms.
Lubis, R. H., & Sari Tarigan, P. (2023). Pengaruh Penggunaan Big Data terhadap Kualitas Audit. AFoSJ-LAS, 3(4). https://j-las.lemkomindo.org/index.php/AFoSJ-LAS/index
McKinsey and Company. (2023). Riset: AI Mampu Tingkatkan Pendapatan Bisnis Hingga 5%. In R. Bilowo (Ed.), Riset: AI Mampu Tingkatkan Pendapatan Bisnis Hingga 5%. https://miitel.com/id/ai-tingkatkan-pendapatan-bisnis/.
Microsoft Indonesia. (2019, March 12). Adopsi Artificial Intelligence di Indonesia: Pengembangan Talenta Masa Depan.
Munawarah, I. (2023). Pengaruh Kompetensi & Independensi Auditor Terhadap Kualitas Audit Dengan Kompetensi Bukti Audit Sebagai Variabel Intervening. Jurnal Gici Jurnal Keuangan Dan Bisnis, 14(1), 1–15. https://doi.org/10.58890/jkb.v14i1.1
Musa, A. M. H., & Lefkir, H. (2024). The role of artificial intelligence in achieving auditing quality for small and medium enterprises in the Kingdom of Saudi Arabia. International Journal of Data and Network Science, 8(2), 835–844. https://doi.org/10.5267/j.ijdns.2023.12.021
Nadzif, N., Mertha, P., & Durya, A. (2022). Pengaruh Kualitas Audit, Debt Ratio, Ukuran Perusahaan, Audit Lag Terhadap Opini Audit Going Concern. Jurnal Ekonomi, Manajemen, Akuntansi, Bisnis Digital Dan Kewirausahaan. DOI:10.55983/inov.v1i2.118
Noordin, N. A., Hussainey, K., & Hayek, A. F. (2022). The Use of Artificial Intelligence and Audit Quality: An Analysis from the Perspectives of External Auditors in the UAE. Journal of Risk and Financial Management, 15(8). https://doi.org/10.3390/jrfm15080339
Nugroho, R. H., Kusumasari, I. R., Febrianto, V., Farhan N. H, M. A., & Mahardika, M. R. (2024). Strategi Teknologi Artificial Intelligence (AI) dalam Pengambilan Keputusan Bisnis di Era Digital. Jurnal Bisnis Dan Komunikasi Digital, 2(2), 7. https://doi.org/10.47134/jbkd.v2i2.3476
Puthukulam, G., Ravikumar, A., Sharma, R. V. K., & Meesaala, K. M. (2021). Auditors’ perception on the impact of artificial intelligence on professional skepticism and judgment in oman. Universal Journal of Accounting and Finance, 9(5), 1184–1190. https://doi.org/10.13189/ujaf.2021.090527
Rahmawan, D. (2023). Tantangan dan Peluang dalam Pemberitaan terkait AI di Indonesia: Studi kasus Pause Giant AI Experiments: An Open Letter. https://www.researchgate.net/publication/375861005
Ramadhan Mukhtar, M., Andi Muhammad Syahrul, & Ahmad Habibi. (2023). Penerapan Audit Berbasis Artificial Intelligence di Indonesia: Sebuah Metasintetis. Journal of Economic Education and Entrepreneurship Studies, 4(2), 711–728. https://doi.org/10.26858/je3s.v4i2.1852
Rizky Wicaksono, S. (2022). Teori Dasar Technology Acceptance Model. https://doi.org/10.5281/zenodo.7754254
Sari, Y. M., & Putri, R. (2024). Persepsi Auditor Eksternal Atas Pengaruh Kemudahan dan Kegunaan Artificial Intelligence Terhadap Kualitas Audit. JAK (Jurnal Akuntansi) Kajian Ilmiah Akuntansi, 11(2), 256–270. https://doi.org/10.30656/jak.v11i2.7661
Suryaningrat, Wi. M. (2021). Implementation of Artificial Intelligence in Public Accounting Firm Case Study: EY. Jakarta. .
Tobing, K. S. L., Nur, M., Lantana, D. A., & Digdowiseiso, K. (2023). The Implementation of Artificial Intelligence on Accounting in Indonesia: A Literature Study. In Business and Social Science (IJEMBIS) Peer-Reviewed-International Journal (Vol. 3, Issue 2). https://cvodis.com/ijembis/index.php/ijembis600.https://cvodis.com/ijembis/index.php/ijembis/article/view/254
Yaiprasert, C., & Hidayanto, A. N. (2024). AI-powered ensemble machine learning to optimize cost strategies in logistics business. International Journal of Information Management Data Insights, 4(1). https://doi.org/10.1016/j.jjimei.2023.100209
Yang, C., Tian, H., & Liu, Y. (2024). Advanced Artificial Intelligence Drivers and IoT Network Systems for Data Collection and Network Transmission in the Industry 5.0 Era. International Journal of High-Speed Electronics and Systems. https://doi.org/10.1142/S012915642540124X




.png)
.png)