Hide
Show all
Email this article Revitalizing Government Internal Auditor Apparatus in the Era of Industry 4.0
Abstract
The purpose of this paper is to propose a transformation strategy which is the focus of the Government Internal Supervisory Apparatus (APIP) on the impact of Industry 4.0 on the internal audit function and the development of an improvement plan for the Internal Auditor SPIP level . can be applied to address audit challenges in the Industry 4.0 era. Due to the impact of Industry 4.0 on audit activities, APIP is required to be able and quickly adapt to technological advances. The adoption of Industry 4.0 technology positions APIP as an activity analyst who can identify errors in business processes and devise solutions to fix them. As a consequence, an APIP transformation strategy is needed to face the challenges of Industry 4.0. The author suggests that the APIP transformation strategy to increase the SPIP level must include: (1) the use of data collection equipment, such as sensors and software, to collect data; (2) inclusion of characteristics that characterize APIP's ability to complete audit tasks, including cognitive abilities, problem solving abilities, communication skills, internal control systems, and agility; and (3) applying a professional, millennial, innovative approach that prioritizes integrity, objectivity and professionalism while still embracing the possibility of failure.
Full Text:
PDFReferences
Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big data and analytics in the modern audit engagement: Research needs. Auditing, 36(4), 1–27. https://doi.org/10.2308/ajpt-51684
Bogataya, I. N., & Evstaf’eva, E. M. (2020). Research on the Evolution of Methodological Approaches to Accounting and Auditing of Estimated Values in the Context of Digitalization. Accounting. Analysis. Auditing, 7(6), 64–74. https://doi.org/10.26794/2408-9303-2020-7-6-64-74
Borgi, H. (2022). XBRL technology adoption and consequences: A synthesis of theories and suggestions of future research. Journal of Accounting and Management Information Systems, 21(2), 220–235. https://doi.org/10.24818/jamis.2022.02004
Camarinha-Matos, L. M., Baldissera, T. A., Di Orio, G., & Marques, F. (2015). Technological innovation for cloud-based engineering systems: 6th IFIPWG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2015 Costa de Caparica, Portugal, April 13-15, 2015 Proceedings. IFIP Advances in Information and Communication Technology, 450(March 2015), I–II. https://doi.org/10.1007/978-3-319-16766-4
Ejoh, N., & Ejom, P. (2014). The Impact of Internal Control Activities on Financial Performance of Tertiary Institutions in Nigeria. Journal of Economics and Sustainable Development, 5(16), 133–144.
Elzarka, S., & Transport, M. (2022). Investigating the Barriers of the Internet of Things. July 2021.
Firmansyah, A., Khairunnisa, D., Gistiani, T. L., & Chaniago, P. R. (2023). the Readiness of the Government Internal Supervisory Apparatus (Apip) for Continuous Auditing Implementation. IPSAR (International Public Sector Accounting Review), 1(1). https://doi.org/10.31092/ipsar.v1i1.2094
Gorecky, D., Schmitt, M., Loskyll, M., & Zühlke, D. (2014). Human-machine-interaction in the industry 4.0 era. Proceedings - 2014 12th IEEE International Conference on Industrial Informatics, INDIN 2014, 289–294. https://doi.org/10.1109/INDIN.2014.6945523
Hermann, M., Pentek, T., & Otto, B. (2015). Design Principles for Industrie 4.0 Scenarios: A Literature Review. Technische Universitat Dortmund, 1(1), 4–16. https://doi.org/10.13140/RG.2.2.29269.22248
Hin, L. T. W., & Subramaniam, R. (2008). e-Government: implementation policies and best practices from Singapore. In Electronic Government: Concepts, Methodologies, Tools, and Applications (pp. 1892–1908). IGI Global.
Ilanković, N., Zelić, A., Gubán, M., & Szabó, L. (2020). Smart factories – the product of Indrusty 4.0. Prosperitas, 7(1), 19–31. https://doi.org/10.31570/prosp_2020_01_2
Jans, M., Alles, M., & Vasarhelyi, M. (2013). The case for process mining in auditing: Sources of value added and areas of application. International Journal of Accounting Information Systems, 14(1), 1–20. https://doi.org/10.1016/j.accinf.2012.06.015
Joshi, P. L., & Marthandan, G. (2020). Continuous internal auditing: Can big data analytics help? International Journal of Accounting, Auditing and Performance Evaluation, 16(1), 25–42. https://doi.org/10.1504/IJAAPE.2020.106766
Ke, W., & Wei, K. K. (2004). Successful e-government in Singapore. Communications of the ACM, 47(6), 95–99.
Kim, Y., & Vasarhelyi, M. A. (2012). A model to detect potentially fraudulent/abnormal wires of an insurance company: An unsupervised rule-based approach. Journal of Emerging Technologies in Accounting, 9(1), 95–110. https://doi.org/10.2308/jeta-50411
Leurent, H., & Abbosh, O. (2018). Driving the Sustainability of Production Systems with Fourth Industrial Revolution Innovation. World Economic Forum (WEF), January, 58. http://www3.weforum.org/docs/WEF_39558_White_Paper_Driving_the_Sustainability_of_Production_Systems_4IR.pdf
Liu, Q., & Vasarhelyi, M. A. (2014). Big questions in AIS research: Measurement, information processing, data analysis, and reporting. Journal of Information Systems, 28(1), 1–17. https://doi.org/10.2308/isys-10395
Marcos A. Pisching, Fabricio Junqueira, Diolino J. dos Santos Filho, & Paulo E. Miyagi. (2015). an Architecture for Organizing and Locating Services To the Industry 4.0. Proceedings of the 23rd ABCM International Congress of Mechanical Engineering, January 2016, 0–8. https://doi.org/10.20906/cps/cob-2015-0415
Mariyam, A., Basha, S. A. H., & Raju, S. V. (2022). Industry 4.0: augmented reality in smart manufacturing industry environment to facilitate faster and easier work procedures. Cloud Analytics for Industry 4.0, June,
Merdzan, G. (2021). Lessons Learned from the Fourth Industrial Revolution for the Global Economy. Knowledge International Journal, 43(1), 85–95.
Moffitt, K. C., & Vasarhelyi, M. A. (2013). AIS in an age of big data. Journal of Information Systems, 27(2), 1–19. https://doi.org/10.2308/isys-10372
O’hEocha, C., Wang, X., & Conboy, K. (2012). The use of focus groups in complex and pressurised IS studies and evaluation using Klein & Myers principles for interpretive research. Information Systems Journal, 22(3), 235–256.
Oleiwi, R. (2023). the Extent To Which Textbooks Fulfill the Requirements of Digital Transformation in Accounting and Auditing. International Journal of Professional Business Review, 8(5), 1–12. https://doi.org/10.26668/businessreview/2023.v8i5.1509
Rahayu, S., Yudi, S., & Rahayu, S. (2020). Internal auditors role indicators and their support of good governance. Cogent Business and Management, 7(1). https://doi.org/10.1080/23311975.2020.1751020
Rakipi, R., De Santis, F., & D’Onza, G. (2021). Correlates of the internal audit function’s use of data analytics in the big data era: Global evidence. Journal of International Accounting, Auditing and Taxation, 42, 100357. https://doi.org/10.1016/j.intaccaudtax.2020.100357
Rikhardsson, P., & Dull, R. (2016). An exploratory study of the adoption, application and impacts of continuous auditing technologies in small businesses. International Journal of Accounting Information Systems, 20, 26–37. https://doi.org/10.1016/j.accinf.2016.01.003
Setianingsih, F. E., Hendarman, A. F., Sulyani, A. C., & Larasati, N. (2023). The Relationship between Human Capital Readiness in the Era 4.0 and Digital Culture towards Employee Performance: A Case Study of Unit X in PT Telekomunikasi Indonesia. International Journal of Current Science Research and Review, 06(01), 34–39. https://doi.org/10.47191/ijcsrr/v6-i1-04
Sutton, S. G., Khazanchi, D., Hampton, C., & Arnold, V. (2008). Risk analysis in extended enterprise environments: Identification of critical risk factors in B2B e-commerce relationships. Journal of the Association for Information Systems, 9(3–4), 151–174.
Werner, M., Wiese, M., & Maas, A. (2021). Embedding process mining into financial statement audits. International Journal of Accounting Information Systems, 41(April). https://doi.org/10.1016/j.accinf.2021.100514
Yaremyk, M. I., & Yaremyk, K. Y. (2021). The Impact of Big Data Analytics and Innovative Information Technologies on Audit Quality. Business Inform, 5(520), 302–307. https://doi.org/10.32983/2222-4459-2021-5
DOI: https://doi.org/10.31294/widyacipta.v8i1.18068
Copyright (c) 2024 Muh Ridwan Basri
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Index by:
 |  |  |  |
 |  |  |  |
 |  |  |
Published LPPM Universitas Bina Sarana Informatika with supported by Relawan Jurnal Indonesia
Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Jakarta Pusat, DKI Jakarta 10450, Indonesia
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License