Model Deteksi Kecurangan Berbasis Fraud Triangle

Abstract

The case of issuers violation in stock market is one of the most frequent case that should be
solved by the stock market’s Regulator Board. In Indonesia, the authority to do the surveillance in
stock exchanges is handled by the Capital Market Supervisory Agency and Financial Institution
(or called ‘Bapepam-LK’ in Indonesian). There is a gap between society’s expectation toward
Bapepam-LK as the regulator and its performance in solving several companies violation cases
which demands some alternative solutions. Based on the above description, this study will
empirically investigate the development of fraud detection model using fraud triangle based on
the cases of violation committed by public companies in Indonesia. In detail, the problems in
this research are: (1) Is there any difference related to the triggering factors of Fraud Triangle
between the company that commits fraud and the company that does not; (2) Is there any difference
in terms of pressure between the company that commits fraud and the company that does not;
(3) Is there any difference in terms of opportunity between the company that commits fraud and
the company that does not; (4) Is there any difference in terms of rationalization between the
company that commits fraud and the company that does not. This research was carried out to the
public companies who are registered in Indonesia Stock Exchanges (BEJ). Generally, there are
two sample group in this research. The first sample group consiststed of the companies who had
committed fraud and the second group as comparison consisted of the non-fraud companies. In
this research there are 98 companies as the research samples which consisted of 23 companies
who had committed fraud and 75 companies who did not commit fraud. The analysis tool used
for this research was logistic regression because the measurements of dependent variable used
the categorical that is dummy variable, code (0) was used for the non-fraud companies and code
(1) was used to indicate the companies who committed fraud. The research result shows that from
four hypothesis proposed in this research, only one variable which fits in to the model (variable
in equation) because posesses the significance score above 0.05. The interpretation is that the
higher the audit report (rationalization), will make the company’s probability to commit fraud is
also higher. From the above explanation, it can be concluded that the fourth hypothesis (H4) is
accepted because the audit report (rationalization) is proven to have the ability in forming the
model to predict fraud in a company.