Determinan niat auditor BPK RI untuk menggunakan teknologi audit berbasis analisis big data
DOI:
https://doi.org/10.30595/kompartemen.v22i2.23181Keywords:
Big Data Analytics, System Quality, Performance Expectations, Perceived Usefulness, AuditAbstract
This study aims to examine the factors that influence the intention of BPK RI auditors to want to use big data analysis methods in audit practice including system quality, performance expectations, and perceived usefulness. This study uses a questionnaire survey method with a sample consisting of BPK RI auditors throughout Indonesia. Respondents were then selected purposively with the criteria that auditors had used big data analysis in conducting audits. The number of auditors who participated in this study was 126 people. Hypothesis testing using Partial Least Square (PLS) technique. The results showed that system quality and performance expectations have a positive effect on perceived usefulness, and perceived usefulness has a positive effect on the intention to use big data analysis-based audit technology.References
Ahmad, F. (2019). Tinjauan sistematis tentang peran Analisis Big Data dalam mengurangi pengaruh kesalahan kognitif pada penilaian audit. Dalam Revista de Contabilidad-Spanish Accounting Review (Vol. 22, Edisi 2, hlm. 187–202). Universitas Murcia. https://doi.org/10.6018/rcsar.382251
Ahmed, HMS, El-Halaby, S., & Albitar, K. (2023). Tata kelola dewan dan keterlambatan laporan audit sehubungan dengan penerapan big data: kasus Mesir. Jurnal Internasional Akuntansi dan Manajemen Informasi , 31 (1), 148–169. https://doi.org/10.1108/IJAIM-04-2022-0088
Ali Memon, M., Ting, H., Cheah, J.-H., Thurasamy, R., Chuah, F., & Huei Cham, T. (2020). Jurnal Pemodelan Persamaan Struktural Terapan UKURAN SAMPEL UNTUK PENELITIAN SURVEI: TINJAUAN DAN REKOMENDASI. Dalam Jurnal Pemodelan Persamaan Struktural Terapan (Vol. 4, Edisi 2).
Aljumah, AI, Nuseir, MT, & Alam, MM (2021a). Kinerja organisasi dan kemampuan menganalisis big data: apakah keterampilan ambidextrous dan nilai bisnis dari analisis big data penting? Jurnal Manajemen Proses Bisnis , 27 (4), 1088–1107. https://doi.org/10.1108/BPMJ-07-2020-0335
Aljumah, AI, Nuseir, MT, & Alam, MM (2021b). Analisis pemasaran tradisional, analisis big data, dan kualitas sistem big data serta keberhasilan pengembangan produk baru. Jurnal Manajemen Proses Bisnis , 27 (4), 1108–1125. https://doi.org/10.1108/BPMJ-11-2020-0527
Aljumah, AI, Nuseir, MT, & Alam, MM (2021c). Analisis pemasaran tradisional, analisis big data, dan kualitas sistem big data serta keberhasilan pengembangan produk baru. Jurnal Manajemen Proses Bisnis , 27 (4), 1108–1125. https://doi.org/10.1108/BPMJ-11-2020-0527
Al-Okaily, A., Al-Okaily, M., & Teoh, AP (2023). Mengevaluasi keberhasilan sistem ERP: bukti dari perusahaan-perusahaan Yordania di era bisnis digital. Jurnal VINE Sistem Manajemen Informasi dan Pengetahuan , 53 (6), 1025–1040. https://doi.org/10.1108/VJIKMS-04-2021-0061
Alyousef, IY (2023). Penerimaan e-learning dalam pendidikan tinggi: Peran kesesuaian tugas-teknologi dengan model keberhasilan sistem informasi. Heliyon , 9 (3). https://doi.org/10.1016/j.heliyon.2023.e13751
Bitrián, P., Buil, I., Catalán, S., & Merli, D. (2024). Gamifikasi dalam pelatihan tenaga kerja: Meningkatkan efikasi diri karyawan, keamanan informasi, dan perilaku perlindungan data. Jurnal Riset Bisnis , 179. https://doi.org/10.1016/j.jbusres.2024.114685
Bouteraa, M., Raja Hisham, RRI, & Zainol, Z. (2023). Tantangan yang mempengaruhi niat nasabah bank untuk mengadopsi teknologi perbankan hijau di UEA: pendekatan metode campuran berbasis UTAUT. Jurnal Pemasaran Islam , 14 (10), 2466–2501. https://doi.org/10.1108/JIMA-02-2022-0039
Brown-Liburd, H., Issa, H., & Lombardi, D. (2015). Implikasi perilaku dari dampak big data terhadap penilaian audit dan pengambilan keputusan serta arah penelitian di masa mendatang. Cakrawala Akuntansi , 29 (2), 451–468. https://doi.org/10.2308/acch-51023
Chen, MF, & Lin, NP (2018). Penggabungan kesadaran kesehatan ke dalam model kesiapan dan penerimaan teknologi untuk memprediksi pengunduhan dan penggunaan aplikasi. Penelitian Internet , 28 (2), 351–373. https://doi.org/10.1108/IntR-03-2017-0099
Chin, WW (1998). Komentar: Isu dan Opini tentang Pemodelan Persamaan Struktural. MIS Quarterly , 22 (1), vii–xvi. http://www.jstor.org/stable/249674
Cimbaljević, M., Demirović Bajrami, D., Kovačić, S., Pavluković, V., Stankov, U., & Vujičić, M. (2023). Adopsi teknologi oleh karyawan dalam konteks pengembangan pariwisata cerdas: peran penerimaan teknologi dan kesiapan teknologi. Jurnal Manajemen Inovasi Eropa . https://doi.org/10.1108/EJIM-09-2022-0516
Dagilienė, L., & Klovienė, L. (2019). Motivasi untuk menggunakan big data dan analisis big data dalam audit eksternal. Managerial Auditing Journal , 34 (7), 750–782. https://doi.org/10.1108/MAJ-01-2018-1773
Davis, FD, Bagozzi, RP, & Warshaw, PR (1989). Penerimaan Pengguna terhadap Teknologi Komputer: Perbandingan Dua Model Teoretis. Ilmu Manajemen , 35 (8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
De Santis, F., & D'Onza, G. (2020). Big data dan analisis data dalam audit: mencari legitimasi. Meditari Accountancy Research , 29 (5), 1088–1112. https://doi.org/10.1108/MEDAR-03-2020-0838
DeLone, WH, & McLean, ER (2003). Model keberhasilan sistem informasi DeLone dan McLean: Pembaruan sepuluh tahun. Jurnal Sistem Informasi Manajemen , 19 (4), 9–30. https://doi.org/10.1080/07421222.2003.11045748
DeLone, WH, & McLean, ER (2016). Pengukuran Keberhasilan Sistem Informasi. Foundations and Trends® dalam Sistem Informasi , 2 (1), 1–116. https://doi.org/10.1561/2900000005
Ditkaew, K., & Suttipun, M. (2023). Dampak analisis data audit terhadap kualitas audit dan kontinuitas tinjauan audit di Thailand. Asian Journal of Accounting Research , 8 (3), 269–278. https://doi.org/10.1108/AJAR-04-2022-0114
Elkmash, MRM, Abdel-Kader, MG, & Badr El Din, B. (2022a). Investigasi eksperimental tentang dampak penggunaan analisis big data terhadap pengukuran kinerja pelanggan. Jurnal Riset Akuntansi , 35 (1), 37–54. https://doi.org/10.1108/ARJ-04-2020-0080
Elkmash, MRM, Abdel-Kader, MG, & Badr El Din, B. (2022b). Investigasi eksperimental tentang dampak penggunaan analisis big data terhadap pengukuran kinerja pelanggan. Jurnal Riset Akuntansi , 35 (1), 37–54. https://doi.org/10.1108/ARJ-04-2020-0080
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146
Ferri, L., Spanò, R., Ginesti, G., & Theodosopoulos, G. (2020). Ascertaining auditors’ intentions to use blockchain technology: evidence from the Big 4 accountancy firms in Italy. Meditari Accountancy Research, 29(5), 1063–1087. https://doi.org/10.1108/MEDAR-03-2020-0829
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Gefen, D., & Straub, D. (2005). A Practical Guide to Factorial Validity Using PLS-Graph: Tutorial and Annotated Example. Communications of the Association for Information Systems, 16, 91–109. https://doi.org/10.17705/1CAIS.01605
Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40, 102–115. https://doi.org/10.1016/j.acclit.2017.05.003
Gündüz, A. Y., & Akkoyunlu, B. (2019). Student views on the use of flipped learning in higher education: A pilot study. Education and Information Technologies, 24(4), 2391–2401. https://doi.org/10.1007/s10639-019-09881-8
Hair, J., Anderson, R., Tatham, R., & Black, W. (2007). Multivariate Analysis 5th Edition.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. In European Business Review (Vol. 31, Issue 1, pp. 2–24). Emerald Group Publishing Ltd. https://doi.org/10.1108/EBR-11-2018-0203
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. In European Business Review (Vol. 26, Issue 2, pp. 106–121). Emerald Group Publishing Ltd. https://doi.org/10.1108/EBR-10-2013-0128
Hair, J., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM).
Hasan, S., Godhuli, E. R., Rahman, M. S., & Mamun, M. A. Al. (2023). The adoption of conversational assistants in the banking industry: is the perceived risk a moderator? Heliyon, 9(9). https://doi.org/10.1016/j.heliyon.2023.e20220
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182–209. https://doi.org/10.1177/1094428114526928
Honggo, F., Handayani, P. W., & Azzahro, F. (2022). The antecedents of intention to use immunization information systems and usage behavior. Informatics in Medicine Unlocked, 34. https://doi.org/10.1016/j.imu.2022.101107
Idayani, R. W., & Darmaningrat, E. W. T. (2024). Evaluation of factors affecting student acceptance of Zedemy using the Unified Theory of Acceptance and Use of Technology (UTAUT). Procedia Computer Science, 234, 1276–1287. https://doi.org/10.1016/j.procs.2024.03.125
Jo, H. (2022). Antecedents of Continuance Intention of Social Networking Services (SNS): Utilitarian, Hedonic, and Social Contexts. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/7904124
Liew, A., Boxall, P., & Setiawan, D. (2022). The transformation to data analytics in Big-Four financial audit: what, why and how? Pacific Accounting Review, 34(4), 569–584. https://doi.org/10.1108/PAR-06-2021-0105
Lin, C.-H., Shih, H.-Y., & Sher, P. J. (2007). Integrating technology readiness into technology acceptance: The TRAM model. Psychology & Marketing, 24(7), 641–657. https://doi.org/https://doi.org/10.1002/mar.20177
Lugli, E., & Bertacchini, F. (2023). Audit quality and digitalization: some insights from theItalian context. Meditari Accountancy Research, 31(4), 841–860. https://doi.org/10.1108/MEDAR-08-2021-1399
Luo, Y., Lin, J., & Yang, Y. (2021). Students’ motivation and continued intention with online self-regulated learning: A self-determination theory perspective. Zeitschrift Fur Erziehungswissenschaft, 24(6), 1379–1399. https://doi.org/10.1007/s11618-021-01042-3
Lutfi, A. (2023). Factors affecting the success of accounting information system from the lens of DeLone and McLean IS model. International Journal of Information Management Data Insights, 3(2), 100202. https://doi.org/10.1016/J.JJIMEI.2023.100202
Merhi, M. I., & Bregu, K. (2020). Effective and efficient usage of big data analytics in public sector. Transforming Government: People, Process and Policy, 14(4), 605–622. https://doi.org/10.1108/TG-08-2019-0083
Moraes, G. H. S. M. de, Pelegrini, G. C., de Marchi, L. P., Pinheiro, G. T., & Cappellozza, A. (2022). Antecedents of big data analytics adoption: an analysis with future managers in a developing country. Bottom Line, 35(2–3), 73–89. https://doi.org/10.1108/BL-06-2021-0068
Negm, E. M. (2023). Consumers’ acceptance intentions regarding e-payments: a focus on the extended unified theory of acceptance and use of technology (UTAUT2). Management & Sustainability: An Arab Review. https://doi.org/10.1108/msar-04-2023-0022
Ng, L., Osborne, S., Eley, R., Tuckett, A., & Walker, J. (2024). Exploring nursing students’ perceptions on usefulness, ease of use, and acceptability of using a simulated Electronic Medical Record: A descriptive study. Collegian, 31(2), 120–127. https://doi.org/10.1016/j.colegn.2023.12.006
Pande, D., & Taeihagh, A. (2024). A governance perspective on user acceptance of autonomous systems in Singapore. Technology in Society, 77. https://doi.org/10.1016/j.techsoc.2024.102580
Putro, A. K., & Takahashi, Y. (2024). Entrepreneurs’ creativity, information technology adoption, and continuance intention: Mediation effects of perceived usefulness and ease of use and the moderation effect of entrepreneurial orientation. Heliyon, 10(3). https://doi.org/10.1016/j.heliyon.2024.e25479
Rahman, M. J., & Ziru, A. (2023). Clients’ digitalization, audit firms’ digital expertise, and audit quality: evidence from China. International Journal of Accounting and Information Management, 31(2), 221–246. https://doi.org/10.1108/IJAIM-08-2022-0170
Ram, J., Corkindale, D., & Wu, M.-L. (2013). Implementation critical success factors (CSFs) for ERP: Do they contribute to implementation success and post-implementation performance? International Journal of Production Economics, 144(1), 157–174. https://doi.org/https://doi.org/10.1016/j.ijpe.2013.01.032
Saleh, I., Marei, Y., Ayoush, M., & Abu Afifa, M. M. (2023). Big Data analytics and financial reporting quality: qualitative evidence from Canada. Journal of Financial Reporting and Accounting, 21(1), 83–104. https://doi.org/10.1108/JFRA-12-2021-0489
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial Least Squares Structural Equation Modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of Market Research (pp. 1–40). Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_15-1
Sekaran, U., & Bougie, R. (2019). Metode Penelitian untuk Bisnis: Pendekatan Pengembangan Keterampilan . John Wiley & Putra.
Sihombing, RP, Narsa, IM, & Harymawan, I. (2023). Analisis big data dan penilaian auditor: studi eksperimental. Jurnal Riset Akuntansi , 36 (2–3), 201–216. https://doi.org/10.1108/ARJ-08-2022-0187
Srivastava, S., Mohta, A., & Shunmugasundaram, V. (2024). Adopsi layanan FinTech pembayaran digital oleh pengguna Gen Y dan Gen Z: bukti dari India. Kebijakan Digital, Regulasi, dan Tata Kelola , 26 (1), 95–117. https://doi.org/10.1108/DPRG-07-2023-0110
Tam, C., & Oliveira, T. (2016). Memahami dampak m-banking terhadap kinerja individu: perspektif DeLone & McLean dan TTF. Komputer dalam Perilaku Manusia , 61 , 233–244. https://doi.org/10.1016/J.CHB.2016.03.016
Venkatesh, V., Morris, MG, Davis, GB, & Davis, FD (2003). Penerimaan Pengguna terhadap Teknologi Informasi: Menuju Pandangan Terpadu. MIS Triwulanan , 27 (3), 425–478. https://doi.org/10.2307/30036540Downloads
Additional Files
Published
How to Cite
Issue
Section
License
Copyright
You are free to:
Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit appropriate credit, provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
License
1. License to Publish
The article will be governed by the Attribution 4.0 International (CC BY 4.0). The author hereby grants Kompartemen an exclusive publishing and distribution license in the manuscript include tables, illustrations or other material submitted for publication as part of the manuscript (the “Article”) in print, electronic and all other media (whether now known or later developed), in any form, in all languages, throughout the world, for the full term of copyright, and the right to license others to do the same, effective when the article is accepted for publication. This license includes the right to enforce the rights granted hereunder against third parties.
2. Author’s Warranties
The author warrants that the article is original, written by stated author/s, has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author(s).
3. User Rights
Under the Creative Commons Attribution 4.0 International (CC BY 4.0) license, the author(s) and users are free to share (copy and redistribute the material in any medium or format for any purpose, even commercially.) and adapt (remix, transform, and build upon the material for any purpose, even commercially.). Users must give appropriate credit, provide a link to the license, and indicate if changes were made.
4. Rights of Authors
Authors retain the following rights:
Copyright, and other proprietary rights relating to the article, such as patent rights,
The right to use the substance of the article in future own works, including lectures and books,
The right to reproduce the article for own purposes, provided the copies are not offered for sale, and
The right to self-archive the article.
5. Co-Authorship
If the article was prepared jointly with other authors, the signatory of this form warrants that he/she has been authorized by all co-authors to sign this agreement on their behalf, and agrees to inform his/her co-authors of the terms of this agreement.
6. Royalties
This agreement entitles the author to no royalties or other fees. To such extent as legally permissible, the author waives his or her right to collect royalties relative to the article in respect of any use of the article by Kompartemen or its sublicensee.
7. Miscellaneous
Kompartemen will publish the article (or have it published) in the Journal if the article’s editorial process is successfully completed and Kompartemen or its sublicensee has become obligated to have the article published. Kompartemen Experiences may conform the article to a style of punctuation, spelling, capitalization, and usage that it deems appropriate.












