The Whistleblowing System, Literacy of Big Data Analytics, and Tax Avoidance: Experimental Study - Agrippina Galuh Sulistyaningrum; R. Nelly Nur Apandi; Alfira Sofia (Future Science, 2020)
Awareness of the existence of a system that can monitor non-compliance will certainly affect the behavior of taxpayers. Testing taxpayers' intentions to avoid taxes because of the whistleblowing system and big data analytics literacy is very relevant due to being in the era of 4.0. The purpose of this research is to find out the differences in taxpayer decisions to avoid taxes based on the whistleblowing system implemented by the Directorate General of Taxes (DJP) and big data ana-lytics literacy. The test is conducting an experimental method with a 2x2 factorial design. Researchers experimented with student respondents who consisted of several groups with certain treatments. To test the main effect and interaction effect hypotheses between the variables studied, used the Two Way ANOVA analysis technique. The results showed that the main influence and interaction proved sig-nificant or not. Taxpayers' actions in tax avoidance can be minimized when the DJP whistleblowing system runs effectively. However, there is no big data analyt-ics literacy effect on tax avoidance, and there is no interaction effect between fac-tors. The uneven literacy of big data analytics among taxpayers in Indonesia will certainly change shortly. So, the DJP should make more optimal use of advances in science and information technology to increase its tax revenue target.