Effect of Evidence Sequencing and Big Data Analytics Knowledge on Risk Assessment Accuracy

Illa Susilawati, Rozmita Dewi Yuniarti, Aristanti Widyaningsih

Abstract


This study aims to determine how the sequence of evidence and knowledge of big data analytics can effect the accuracy of junior auditors in assessing the risk of misstatement. The research method involved experimentation using a 2x2 factorial design. The study was conducted with 66 junior auditors who work in KAP (Public Accounting Firm) located at Bandung, Bekasi, and Jakarta. The empirical results of this study demonstrate that the sequence of evidence and knowledge of big data analytics do have an impact on the accuracy of risk assessment. These findings have implications for public accountants that knowledge about big data analytics can be used to enhance training and education, ultimately leading to improved performance of auditors in the audit process. This research has not been widely associated with the use of big data analytics knowledge as a basis for research. Currently, big data analytics is more commonly utilised as a supplementary study to provide an overview of the era of the Industrial Revolution 4.0

Keywords


Audit Evidence, Big Data Analytics, Risk of Assessment, Sequence of Evidence

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DOI: https://doi.org/10.17509/jpak.v13i1.64294

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