The vast amount of taxpayer and the limited resources in Indonesian Tax Authority (DJP) to monitor the taxpayer, require DJP to plan tax audit optimally. This study aim to analyze the effectifity of Compliance Risk Management (CRM) policy in DJP. This study is using qualitative approach through interview with 7 peoples who have roles in implementing tax policy in Indonesia. This study founds the importance of CRM policy, in which the tax authority cannot apply the same treatment to all taxpayers, so it needs to decide which taxpayer needs to be investigated with rational justification based on risk level. Tax authority needs to focus on implementing CRM as an important source of information in decision making process.
Implementation of tax self-assessment system gives full trust to taxpayers to calculate, pay, and report their tax themselves. To get the optimum result, the implementation of this system is determined by the level of compliance of the taxpayers. It is affected by internal and external factors such as technology, resources, legislation where the tax authority operating, organization’s aim and strategy, and public general tax conformity. This study aim to analyze taxpayer conformity level with machine based Compliance Risk Management (CRM) policy. This study is using qualitative approach through interview with people who have roles in implementing tax policy in Indonesia. This study founds the importance of machine learning based CRM policy, in which the tax authority cannot apply the same treatment to all taxpayers, so it needs to decide which taxpayer needs to be investigated with rational justification based on risk level. Tax authority needs to focus on implementing big data analytics with machine learning algorithm as an important source of information in decision making process, and helps predict taxpayers with potential fraud, so it can be used to reduce task risk before it happens.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.