Pemodelan Deteksi Kecurangan Penyajian Laporan Keuangan Perusahaan Perbankan Menggunakan Regresi Data Panel dengan Pendekatan Fraud Hexagon Theory

Amrina, Feny Ulil (2026) Pemodelan Deteksi Kecurangan Penyajian Laporan Keuangan Perusahaan Perbankan Menggunakan Regresi Data Panel dengan Pendekatan Fraud Hexagon Theory. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Laporan keuangan merupakan instrumen krusial dalam menyajikan kondisi finansial perusahaan, namun dorongan untuk menampilkan performa positif sering kali memicu praktik kecurangan laporan keuangan (financial statement fraud). Berdasarkan standar Association of Certified Fraud Examiners (ACFE), fraud diklasifikasikan menjadi penyalahgunaan aset (asset misappropriation), korupsi (corruption), dan kecurangan laporan keuangan (financial statement fraud). Meskipun kecurangan laporan keuangan merupakan skema yang paling jarang terjadi dibandingkan kategori lainnya, jenis kecurangan ini memberikan dampak kerugian median yang paling besar secara global, dengan sektor perbankan tercatat sebagai kontributor kasus tertinggi. Penelitian ini bertujuan untuk mendeteksi kecurangan laporan keuangan pada perusahaan perbankan yang terdaftar di Bursa Efek Indonesia (BEI) periode 2022–2024 menggunakan pendekatan Fraud Hexagon Theory dan metode regresi data panel. Indikasi kecurangan dalam penelitian ini diukur menggunakan model Beneish M-Score. Hasil perhitungan menunjukkan bahwa secara rata-rata perusahaan perbankan berada pada kategori aman dengan nilai -2,233, namun risiko manipulasi tertinggi tercatat pada tahun 2022 dengan nilai rata-rata -2,176. Hasil analisis regresi data panel dengan model terbaik Random Effect Model (REM) menunjukkan bahwa variabel Stimulus (X_1)berpengaruh positif secara signifikan dan variabel Opportunity (X_3) berpengaruh negatif secara signifikan terhadap kecurangan laporan keuangan. Sementara itu, variabel Capability (X_2), Rationalization (X_4), Ego (X_5), dan Collusion (X_6) tidak memiliki pengaruh signifikan terhadap model. Nilai koefisien determinasi menunjukkan bahwa variabel independen mampu menjelaskan variabilitas kecurangan sebesar 5,93%, sedangkan 94,07% sisanya dijelaskan oleh faktor lain di luar model.
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Financial statements are crucial instruments for presenting a company's financial condition. However, the drive to demonstrate positive performance often leads to financial statement fraud. According to the Association of Certified Fraud Examiners (ACFE) standards, fraud is classified into asset misappropriation, corruption, and financial statement fraud. Although financial statement fraud is the least common type of fraud, it results in the highest median loss globally, with the banking sector accounting for the highest number of cases. This study aims to detect financial statement fraud in banking companies listed on the Indonesia Stock Exchange (IDX) for the 2022–2024 period using the Fraud Hexagon Theory approach and panel data regression methods. Fraud indicators in this study were measured using the Beneish M-Score model. The results indicate that, on average, banking companies are in the safe category with a score of -2.233, but the highest risk of manipulation was recorded in 2022 with an average score of -2.176. The results of panel data regression analysis using the best Random Effects Model (REM) indicate that the Stimulus variable (X_1) has a significant positive effect, and the Opportunity variable (X_3) has a significant negative effect on financial statement fraud. Meanwhile, the Capability (X_2), Rationalization (X_4), Ego (X_5), and Collusion (X_6), variables do not have a significant effect on the model. The coefficient of determination indicates that the independent variables can explain 5.93% of the variability in fraud, while the remaining 94.07% is explained by other factors outside the model.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Beneish M-Score, Fraud Hexagon Theory, Kecurangan Laporan Keuangan, Regresi Data Panel, Sektor Perbankan. Banking Sector, Beneish M-Score, Financial Statement Fraud, Fraud Hexagon Theory, Panel Data Regression
Subjects:	H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis.
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Feny Ulil Amrina
Date Deposited:	03 Feb 2026 03:01
Last Modified:	03 Feb 2026 03:01
URI:	http://repository.its.ac.id/id/eprint/130994

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