📅 01 December 2021
DOI: 10.34152/fe.16.2.455 - 471

A BIBLIOMETRIC ANALYSIS AND VISUALIZATION OF ACCOUNTING FRAUD DETECTION USING MACHINE LEARNING RESEARCH

Fokus Ekonomi : Jurnal Ilmiah Ekonomi
Sekolah Tinggi Ilmu Ekonomi Pelita Nusantara

📄 Abstract

Background: Machine Learning technology used in the field of accounting has been widely studied by scholars all over the world. But there is little research on Accounting Fraud Detection Using Machine Learning (AFDUM) from the perspectives of bibliometrics and visualization, and the research topics and development trends in this field are still unclear.Methods: This paper has applied bibliometric visualization software tools, R-Biblioshiny Package, to study the citation characteristics, international cooperation, author cooperation, and geographical distribution of the Accounting Fraud Detection Using Machine Learning (AFDUM). Finding:The literature data involved in this study are retrieved form the core collection of SCOPUS. A total 320 document are obtained, and the most frequent document type is article of Business Management & Accounting subject area (181), Computer Science subject area (144), Economics, Econometrics and Finance (103), Decision Science (78), Social Sciences(47) The bibliometric results reveal in terms of science mapping that the publications over the last 6 years (2015-2022) can be summarized to be focused in five research streams (1)financial system, (2)blockchain, (3)crime, (4)deep learning, (5)learning systems, (6)machine learning, (7)anomaly detection, (8)artificial intelligence, (9)risk assesment, (10)data mining  Practical Implications:The paper will identify the leading trends in the journal in terms of papers, authors,institutions, countries, journals, topics and keywords. This study will enable readers achieve full under­standing of the journal.The hot topics in accounting fraud detection there is 3 frontier topics are learning system, financial system, and crime, and would be the foci of future research Conclusion:The present study provides a panoramic view of data mining methods applied in accounting fraud detection by visualization and bibliometrics. Analysis of authors, journals, institutions, and countries could provide reference for researchers who are fresh to the field in different ways. Researchers may also consider the emerging trends when deciding the direction of their study. Originality/Value:The study provides objective evaluation of the jour­nal progress through a decade of its operation; it highlights the achieve­ment and discusses the progress and contribution of the journal to the scientific research.

🔖 Keywords

#bibliometric analysis; bibliometrix; medical data mining; visualization; R-Biblioshiny

ℹ️ Informasi Publikasi

Tanggal Publikasi
01 December 2021
Volume / Nomor / Tahun
Volume 16, Nomor 2, Tahun 2021

📝 HOW TO CITE

Dewayanto, Totok, "A BIBLIOMETRIC ANALYSIS AND VISUALIZATION OF ACCOUNTING FRAUD DETECTION USING MACHINE LEARNING RESEARCH," Fokus Ekonomi : Jurnal Ilmiah Ekonomi, vol. 16, no. 2, Dec. 2021.

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