DETECTION OF FINANCIAL STATEMENT FRAUD: STUDY IN INDONESIA BANKING AND ENERGY SECTOR COMPANIES

Fraud potential in financial statements often occurs. For this reason, this study identifies aspects that cause financial statement fraud (FOFS), including financial targets (FTs), total accruals, and total assets (TATAs), and the industries' nature (NOIs) in the banking and energy sector companies in Indonesia. The data sample is the financial and annual reports of 122 banking and energy companies. The purposive sampling is used for the selection of the data. The analysis uses different test analysis methods and panel data regression tests. The results prove that FTs prove to be a strong predictor of FOFS in banking companies, while in energy companies it is not proven. Furthermore, TATAs have not been proven to affect FOFS in companies in both sectors. Meanwhile, NOIs have a negative effect on FOFS. The implication is for the banking sector, the potential for FOFS is more due to the disclosure of high Return on assets (ROA) and low-income ratios. In contrast, in the energy sector, companies are strongly influenced only by low-income ratios.

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Journal
International Journal of Economics Business and Accounting Research (IJEBAR)
Published
2024-10-05
DOI
https://doi.org/10.29040/ijebar.v8i3.13797
Primary Topic
Imbalanced Data Classification Techniques
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article
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article

DETECTION OF FINANCIAL STATEMENT FRAUD: STUDY IN INDONESIA BANKING AND ENERGY SECTOR COMPANIES

Donny Maha Putra, Gilang Jelita Santini
International Journal of Economics Business and Accounting Research (IJEBAR)
Imbalanced Data Classification Techniques
article

DETECTION OF FINANCIAL STATEMENT FRAUD: STUDY IN INDONESIA BANKING AND ENERGY SECTOR COMPANIES

Donny Maha Putra, Gilang Jelita Santini
article en

Abstract

Fraud potential in financial statements often occurs. For this reason, this study identifies aspects that cause financial statement fraud (FOFS), including financial targets (FTs), total accruals, and total assets (TATAs), and the industries' nature (NOIs) in the banking and energy sector companies in Indonesia. The data sample is the financial and annual reports of 122 banking and energy companies. The purposive sampling is used for the selection of the data. The analysis uses different test analysis methods and panel data regression tests. The results prove that FTs prove to be a strong predictor of FOFS in banking companies, while in energy companies it is not proven. Furthermore, TATAs have not been proven to affect FOFS in companies in both sectors. Meanwhile, NOIs have a negative effect on FOFS. The implication is for the banking sector, the potential for FOFS is more due to the disclosure of high Return on assets (ROA) and low-income ratios. In contrast, in the energy sector, companies are strongly influenced only by low-income ratios.

International Journal of Economics Business and Accounting Research (IJEBAR)Vol. 8(3)
Universitas Pembangunan Nasional Veteran Jakarta (ID)
Openalex Percentile: Top 79%
Imbalanced Data Classification Techniques
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DETECTION OF FINANCIAL STATEMENT FRAUD: STUDY IN INDONESIA BANKING AND ENERGY SECTOR COMPANIES — Donny Maha Putra, Gilang Jelita Santini · International Journal of Economics Business and Accounting Research (IJEBAR) (2024) | TGRS Research Map | TGRS