SIAPKAH MAHASISWA AKUNTANSI MENGHADAPI ARTIFICIAL INTELLIGENCE DALAM AKUNTANSI?
Article Sidebar
Published:
Feb 4, 2023
Main Article Content
Abstract
Akuntan adalah salah satu profesi yang diramalkan oleh para ahli akan tergantikan perannya oleh teknologi pada masa yang akan datang. Hal ini tentu saja menjadi tantangan bagi kampus-kampus yang membuka program studi akuntansi dan mahasiswa-mahasiswa akuntansi. Walaupun kondisi tersebut merupakan sebuah ramalan, tetapi ramalan tersebut dihasilkan setelah para ahli melakukan penelitian-penelitian. Faktanya, telah ada beberapa profesi yang mulai berkurang permintaannya, misalnya tenaga supporting dalam industri perbankan. Kondisi inilah yang menyebabkan ramalan-ramalan tersebut bukan isapan jempol semata. Tentu saja tantangan tersebut harus dijawab dengan persiapan-persiapan yang matang, sehingga ketika ramalan itu mulai terwujud, kampus-kampus, mahasiswa-mahasiwa dan lulusan-lulusan program studi akuntansi telah siap menghadapi kondisi tersebut. Penelitian ini bertujuan untuk mengukur sejauh mana mahasiswa program akuntansi mengetahui tantangan tersebut. Dengan mengetahui sejauh mana mengetahui tantangan tersebut, maka kampus-kampus yang membuka program studi akuntansi, khususnya program studi akuntansi di lingkungan Universitas Lancang Kuning mulai merancang dan merencanakan langkah-langkah untuk mengantisipasi tantangan tersebut. Misalnya dengan membuka mata kuliah yang berkaitan dengan Accounting Artificial Intelligence. Hasil penelitian ini menunjukkan bahwa kesiapan teknologi ternyata tidak memiliki pengaruh terhadap pengetahuan teknologi Artificial Intelligence dalam bidang akuntansi.
Article Details
Issue
Section
Articles
References
Albrecht, W. S., & Sack, R. J. (2001). The Perilous Future of Accounting Education. The CPA Journal, 71(3), 16.
Aldredge, M., Rogers, C., & Smith, J. (2021). The Strategic Transformation of Accounting into a Learned Profession. Industry and Higher Education, 35(2), 83–88. https://doi.org/10.1177/0950422220954319
Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411
Awayiga, J. Y., Onumah, J. M., & Tsamenyi, M. (2010). Knowledge and Skills Development of Accounting Graduates : The Perceptions of Graduates and Employers in Ghana. Accounting Education: An International Journal, 19(1–2), 139–158. https://doi.org/10.1080/09639280902903523
Bhaskar, K. N. (1982). Use of Computers in Accountancy Courses. Accounting and Business Research, 13(49), 3–10. https://doi.org/10.1080/00014788.1982.9729724
Burnett, S. (2003). The Future of Accounting Education: A Regional Perspective. Journal of Education for Business, 78(3), 129–134. https://doi.org/10.1080/08832320309599709
Business Insider. (2018). These Are The Jobs That Will Be Safe From The Imminent Invasion Of Robots. Business Insider.
Byrne, M., & Flood, B. (2003). Assessing the Teaching Quality of Accounting Programmes: An Evaluation of the Course Experience Questionnaire. Assessment and Evaluation in Higher Education, 28(2), 135–145. https://doi.org/10.1080/02602930301668
Chin, W. W. (2003). PLS-Graph, Version 3.00 (Build 1130), University of Houston. Houston. TX.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. 1988, Hillsdale, NJ: L. Lawrence Earlbaum Associates, 2.
Damerji, H., & Salimi, A. (2021). Mediating Effect of Use Perceptions on Technology Readiness and Adoption of Artificial Intelligence in Accounting. Accounting Education, 30(2), 107–130. https://doi.org/10.1080/09639284.2021.1872035
Davenport, T. H., & Kirby, J. (2016). Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. Harper Business.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology.
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
De Villiers, R. (2021). Seven Principles to Ensure Future-Ready Accounting Graduates – a Model for Future Research and Practice. Meditari Accountancy Research, 29(6), 1354–1380. https://doi.org/10.1108/MEDAR-04-2020-0867
Engle, T. J., & Joseph, G. W. (1986). A Successful Approach to Integrating Computer Assignments into Accounting Information Systems Courses in a Manner that Complements Theoretical Readings. Journal of Accounting Education, Teaching and Educational Notes, 4(2), 141–146. https://doi.org/10.1016/0748-5751(86)90016-3
Er, M. C., & Ng, A. C. (1989). The Use of Computers in Accountancy Courses: A New Perspective. Accounting and Business Research, 19(76), 319–326. https://doi.org/10.1080/00014788.1989.9728861
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley.
Fishbein, M., & Ajzen, I. (2009). Predicting and Changing Behavior: The Reasoned Action Approach (1st ed.) (1st ed.). Psychology Press.
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/Article
Govil, S. (2020, January). Voices What AI does for accountants. Accounting Today. https://www.accountingtoday.com/opinion/what-ai-does-for-accountants
Hair-Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). SAGE Publication, Inc.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate Data Analysis: A Global Perspective, 7 Pearson. In Upper Saddle River, NJ.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis: Pearson New International Edition (7th ed.). Pearson Education Limited.
Heiat, A., Brown, D., & Johnson, D. M. (2007). An Empirical Analysis of Underlying Factors Affecting The Choice of Accounting Major. Journal of College Teaching & Learning (TLC), 4(8), 83–98. https://doi.org/10.19030/tlc.v4i8.1558
Howieson, B. (2003). Accounting Practice in the New Millennium: Is Accounting Education Ready to Meet the Challenge? In The British Accounting Review (Vol. 35). https://doi.org/10.1016/S0890-8389(03)00004-0
Hulland, J. (1999). Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies. Strategic Management Journal, 20, 195–204.
Kavanagh, M. H., & Drennan, L. (2008). What Skills and Attributes Does an Accounting Graduate Need? Evidence from Student Perceptions and Employer Expectation. Accounting and Finance, 48, 279–300. http://www.scribd.com/doc/17320277/What-skills-and-attributes-does-an-accountinggraduate-%5CnNeed-Evidence-from-student-perceptions-and-employer-expectations
Kokina, J., & Davenport, T. H. (2017). The Emergence of Artificial Intelligence: How Automation is Changing Auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122. https://doi.org/10.2308/jeta-51730
Kovalenko, S. N., Kalutskaya, N. A., Bolvachev, A. I., Prodanova, N. A., Sotnikova, L. V., & Shevchenko, O. P. (2021). Artificial Intelligence in The Accounting Profession. Laplage Em Revista (International), 7, 378–383. https://doi.org/10.24115/s2446-622020217extra-b939p.384-395
Lai, M. L. (2008). Technology Readiness, Internet Self-Efficacy and Computing Experience of Professional Accounting Students. Campus-Wide Information Systems, 25(1), 18–29. https://doi.org/10.1108/10650740810849061
Le Guyader, L. P. (2020). Artificial intelligence in accounting: GAAP’s “FAS133.” Journal of Corporate Accounting and Finance, 31(3), 185–189. https://doi.org/10.1002/jcaf.22407
Lee, C. S., & Tajudeen, F. P. (2020). Usage and Impact of Artificial Intelligence on Accounting: Evidence from Malaysian Organisations. Asian Journal of Business and Accounting, 13(1), 213–239. https://doi.org/10.22452/ajba.vol13no1.8
Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A Profession in Transition: Actors, Tasks and Roles in AI-based Accounting. Journal of Applied Accounting Research, 22(3), 539–556. https://doi.org/10.1108/JAAR-10-2020-0201
Li, C.-F. (2013). The Revised Technology Acceptance Model and the Impact of Individual Differences in Assessing Internet Banking Use in Taiwan. International Journal of Business & Information, 8(1).
Ma, Q., & Liu, L. (2004). The Technology Acceptance Model: A Meta-Analysis of Empirical Findings. Journal of Organizational and End User Computing, 16(1), 59–72. https://doi.org/10.4018/978-1-59140-474-3.ch006
Moore, W. B., & Felo, A. (2022). The Evolution of Accounting Technology Education: Analytics to STEM. Journal of Education for Business, 97(2), 105–111. https://doi.org/10.1080/08832323.2021.1895045
Muawanah, A., Adawiyah, D., Maisarah, I., Ali, M. R. A., & Widiastuti, N. P. E. (2022). Perilaku Auditor Menyikapi Munculnya Artificial Intelligence dalam Proses Audit. Jurnal Publikasi Ekonomi Dan Akuntansi, 2(1), 52–60.
Pan, Y. (2016). Heading Toward Artificial Intelligence 2.0. Engineering, 2(4), 409–413. https://doi.org/10.1016/J.ENG.2016.04.018
Parasuraman, A. (2000). Technology Readiness Index (TRI): A Multipleitem Scale To Measure Readiness To Embrace New Technologies. Journal of Service Research, 2(4), 307–320.
Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59–74. https://doi.org/10.1177/1094670514539730
Qasim, A., & Kharbat, F. F. (2020). Blockchain Technology, Business Data Analytics, and Artificial Intelligence: Use in the Accounting Profession and Ideas for Inclusion into the Accounting Curriculum. Journal of Emerging Technologies in Accounting, 17(1), 107–117. https://doi.org/10.2308/jeta-52649
Rogers, E. M. (1976). New Product Adoption and Diffusion. Journal of Consumer Research, 2(4), 290. https://doi.org/10.1086/208642
Saleh, M. M. A., Jawabreh, O. A. A., Al Om, R., & Shniekat, N. (2021). Artificial Intelligence (AI) and the Impact of Enhancing the Consistency and Interpretation of Financial Statement in the Classified Hotels in Aqaba, Jordan. Academy of Strategic Management Journal, 20(SpecialIssue3), 1–18.
Singh, S., & Singh, S. (2010). Artificial Intelligence. International Journal of Computer Applications, 6(6), 21–23.
Spraakman, G., O’Grady, W., Askarany, D., & Akroyd, C. (2015). Employers’ Perceptions of Information Technology Competency Requirements for Management Accounting Graduates. Accounting Education: An International Journal, 24(5), 403–422. https://doi.org/10.1080/09639284.2015.1089177
Sutton, S. G., Holt, M., & Arnold, V. (2016). “The Reports of My Death are Greatly Exaggerated”—Artificial Intelligence Research in Accounting. International Journal of Accounting Information Systems, 22, 60–73. https://doi.org/10.1016/j.accinf.2016.07.005
Triatmaja, M. F. (2019). Dampak Artificial Intelligence (AI) Pada Profesi Akuntan. Seminar Nasional Dan The 6th Call For Syariah Paper (SANCALL) 2019, 1007–1019.
Wells, P., Gerbic, P., Kranenburg, I., & Bygrave, J. (2009). Professional Skills and Capabilities of Accounting Graduates: The New Zealand Expectation Gap? Accounting Education, 18(4–5), 403–420. https://doi.org/10.1080/09639280902719390
Wijayana, S. (2018). Benarkah Peran Akuntan Digantikan Oleh Teknologi (Informasi)? EB NEWS.
Wold, H. (1980). Model Construction and Evaluation When Theoretical Knowledge Is Scarce. Theory and Application of Partial Least Squares. In Evaluation of Econometric Models (pp. 47–74). https://doi.org/978-0-12-416550-2
Aldredge, M., Rogers, C., & Smith, J. (2021). The Strategic Transformation of Accounting into a Learned Profession. Industry and Higher Education, 35(2), 83–88. https://doi.org/10.1177/0950422220954319
Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411
Awayiga, J. Y., Onumah, J. M., & Tsamenyi, M. (2010). Knowledge and Skills Development of Accounting Graduates : The Perceptions of Graduates and Employers in Ghana. Accounting Education: An International Journal, 19(1–2), 139–158. https://doi.org/10.1080/09639280902903523
Bhaskar, K. N. (1982). Use of Computers in Accountancy Courses. Accounting and Business Research, 13(49), 3–10. https://doi.org/10.1080/00014788.1982.9729724
Burnett, S. (2003). The Future of Accounting Education: A Regional Perspective. Journal of Education for Business, 78(3), 129–134. https://doi.org/10.1080/08832320309599709
Business Insider. (2018). These Are The Jobs That Will Be Safe From The Imminent Invasion Of Robots. Business Insider.
Byrne, M., & Flood, B. (2003). Assessing the Teaching Quality of Accounting Programmes: An Evaluation of the Course Experience Questionnaire. Assessment and Evaluation in Higher Education, 28(2), 135–145. https://doi.org/10.1080/02602930301668
Chin, W. W. (2003). PLS-Graph, Version 3.00 (Build 1130), University of Houston. Houston. TX.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. 1988, Hillsdale, NJ: L. Lawrence Earlbaum Associates, 2.
Damerji, H., & Salimi, A. (2021). Mediating Effect of Use Perceptions on Technology Readiness and Adoption of Artificial Intelligence in Accounting. Accounting Education, 30(2), 107–130. https://doi.org/10.1080/09639284.2021.1872035
Davenport, T. H., & Kirby, J. (2016). Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. Harper Business.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Massachusetts Institute of Technology.
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
De Villiers, R. (2021). Seven Principles to Ensure Future-Ready Accounting Graduates – a Model for Future Research and Practice. Meditari Accountancy Research, 29(6), 1354–1380. https://doi.org/10.1108/MEDAR-04-2020-0867
Engle, T. J., & Joseph, G. W. (1986). A Successful Approach to Integrating Computer Assignments into Accounting Information Systems Courses in a Manner that Complements Theoretical Readings. Journal of Accounting Education, Teaching and Educational Notes, 4(2), 141–146. https://doi.org/10.1016/0748-5751(86)90016-3
Er, M. C., & Ng, A. C. (1989). The Use of Computers in Accountancy Courses: A New Perspective. Accounting and Business Research, 19(76), 319–326. https://doi.org/10.1080/00014788.1989.9728861
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley.
Fishbein, M., & Ajzen, I. (2009). Predicting and Changing Behavior: The Reasoned Action Approach (1st ed.) (1st ed.). Psychology Press.
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/Article
Govil, S. (2020, January). Voices What AI does for accountants. Accounting Today. https://www.accountingtoday.com/opinion/what-ai-does-for-accountants
Hair-Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). SAGE Publication, Inc.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate Data Analysis: A Global Perspective, 7 Pearson. In Upper Saddle River, NJ.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis: Pearson New International Edition (7th ed.). Pearson Education Limited.
Heiat, A., Brown, D., & Johnson, D. M. (2007). An Empirical Analysis of Underlying Factors Affecting The Choice of Accounting Major. Journal of College Teaching & Learning (TLC), 4(8), 83–98. https://doi.org/10.19030/tlc.v4i8.1558
Howieson, B. (2003). Accounting Practice in the New Millennium: Is Accounting Education Ready to Meet the Challenge? In The British Accounting Review (Vol. 35). https://doi.org/10.1016/S0890-8389(03)00004-0
Hulland, J. (1999). Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies. Strategic Management Journal, 20, 195–204.
Kavanagh, M. H., & Drennan, L. (2008). What Skills and Attributes Does an Accounting Graduate Need? Evidence from Student Perceptions and Employer Expectation. Accounting and Finance, 48, 279–300. http://www.scribd.com/doc/17320277/What-skills-and-attributes-does-an-accountinggraduate-%5CnNeed-Evidence-from-student-perceptions-and-employer-expectations
Kokina, J., & Davenport, T. H. (2017). The Emergence of Artificial Intelligence: How Automation is Changing Auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122. https://doi.org/10.2308/jeta-51730
Kovalenko, S. N., Kalutskaya, N. A., Bolvachev, A. I., Prodanova, N. A., Sotnikova, L. V., & Shevchenko, O. P. (2021). Artificial Intelligence in The Accounting Profession. Laplage Em Revista (International), 7, 378–383. https://doi.org/10.24115/s2446-622020217extra-b939p.384-395
Lai, M. L. (2008). Technology Readiness, Internet Self-Efficacy and Computing Experience of Professional Accounting Students. Campus-Wide Information Systems, 25(1), 18–29. https://doi.org/10.1108/10650740810849061
Le Guyader, L. P. (2020). Artificial intelligence in accounting: GAAP’s “FAS133.” Journal of Corporate Accounting and Finance, 31(3), 185–189. https://doi.org/10.1002/jcaf.22407
Lee, C. S., & Tajudeen, F. P. (2020). Usage and Impact of Artificial Intelligence on Accounting: Evidence from Malaysian Organisations. Asian Journal of Business and Accounting, 13(1), 213–239. https://doi.org/10.22452/ajba.vol13no1.8
Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A Profession in Transition: Actors, Tasks and Roles in AI-based Accounting. Journal of Applied Accounting Research, 22(3), 539–556. https://doi.org/10.1108/JAAR-10-2020-0201
Li, C.-F. (2013). The Revised Technology Acceptance Model and the Impact of Individual Differences in Assessing Internet Banking Use in Taiwan. International Journal of Business & Information, 8(1).
Ma, Q., & Liu, L. (2004). The Technology Acceptance Model: A Meta-Analysis of Empirical Findings. Journal of Organizational and End User Computing, 16(1), 59–72. https://doi.org/10.4018/978-1-59140-474-3.ch006
Moore, W. B., & Felo, A. (2022). The Evolution of Accounting Technology Education: Analytics to STEM. Journal of Education for Business, 97(2), 105–111. https://doi.org/10.1080/08832323.2021.1895045
Muawanah, A., Adawiyah, D., Maisarah, I., Ali, M. R. A., & Widiastuti, N. P. E. (2022). Perilaku Auditor Menyikapi Munculnya Artificial Intelligence dalam Proses Audit. Jurnal Publikasi Ekonomi Dan Akuntansi, 2(1), 52–60.
Pan, Y. (2016). Heading Toward Artificial Intelligence 2.0. Engineering, 2(4), 409–413. https://doi.org/10.1016/J.ENG.2016.04.018
Parasuraman, A. (2000). Technology Readiness Index (TRI): A Multipleitem Scale To Measure Readiness To Embrace New Technologies. Journal of Service Research, 2(4), 307–320.
Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index: TRI 2.0. Journal of Service Research, 18(1), 59–74. https://doi.org/10.1177/1094670514539730
Qasim, A., & Kharbat, F. F. (2020). Blockchain Technology, Business Data Analytics, and Artificial Intelligence: Use in the Accounting Profession and Ideas for Inclusion into the Accounting Curriculum. Journal of Emerging Technologies in Accounting, 17(1), 107–117. https://doi.org/10.2308/jeta-52649
Rogers, E. M. (1976). New Product Adoption and Diffusion. Journal of Consumer Research, 2(4), 290. https://doi.org/10.1086/208642
Saleh, M. M. A., Jawabreh, O. A. A., Al Om, R., & Shniekat, N. (2021). Artificial Intelligence (AI) and the Impact of Enhancing the Consistency and Interpretation of Financial Statement in the Classified Hotels in Aqaba, Jordan. Academy of Strategic Management Journal, 20(SpecialIssue3), 1–18.
Singh, S., & Singh, S. (2010). Artificial Intelligence. International Journal of Computer Applications, 6(6), 21–23.
Spraakman, G., O’Grady, W., Askarany, D., & Akroyd, C. (2015). Employers’ Perceptions of Information Technology Competency Requirements for Management Accounting Graduates. Accounting Education: An International Journal, 24(5), 403–422. https://doi.org/10.1080/09639284.2015.1089177
Sutton, S. G., Holt, M., & Arnold, V. (2016). “The Reports of My Death are Greatly Exaggerated”—Artificial Intelligence Research in Accounting. International Journal of Accounting Information Systems, 22, 60–73. https://doi.org/10.1016/j.accinf.2016.07.005
Triatmaja, M. F. (2019). Dampak Artificial Intelligence (AI) Pada Profesi Akuntan. Seminar Nasional Dan The 6th Call For Syariah Paper (SANCALL) 2019, 1007–1019.
Wells, P., Gerbic, P., Kranenburg, I., & Bygrave, J. (2009). Professional Skills and Capabilities of Accounting Graduates: The New Zealand Expectation Gap? Accounting Education, 18(4–5), 403–420. https://doi.org/10.1080/09639280902719390
Wijayana, S. (2018). Benarkah Peran Akuntan Digantikan Oleh Teknologi (Informasi)? EB NEWS.
Wold, H. (1980). Model Construction and Evaluation When Theoretical Knowledge Is Scarce. Theory and Application of Partial Least Squares. In Evaluation of Econometric Models (pp. 47–74). https://doi.org/978-0-12-416550-2