PERAN BIG DATA ANALYTICS DALAM HUBUNGAN PRUDENCE MENGATASI KECURANGAN LAPORAN KEUANGAN

Abstrak

This study aims to examine the role of big data analytics as a moderating variable in the relationship between prudence and financial statement fraud. The research was conducted on Indonesian state-owned companies that went public in 2021-2023. Sample selection using purposive sampling technique. The research design uses descriptive quantitative with multiple linear regression analysis methods. Moderation variables are treated as quasi moderation variables and pure moderation variables. The test results show that prudence has a negative effect (-5.486 and -5.198) on financial statement fraud and is significant at the 10% level in the quasi-moderation model and significant at the 5% level in the pure moderation model. The higher the level of application of the principle of prudence the lower the chance of manipulative behavior. The moderating variable of big data analytics consistently has no effect on the research model either as a quasi-moderating variable or as a moderating variable. This is indicated by a significant value of 0.695 in the quasi-moderation model and 0.683 in the pure moderation model. The implementation of big data analytics in the form of software is still very low. The average use of software in state-owned companies going public only 1% of total assets. The low use of big data analytics causes no significant effect on the research model.