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All Journal Aptisi Transactions on Technopreneurship (ATT) ADI Journal on Recent Innovation (AJRI)
Putra, Souza Nurafrianto Windiartono
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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Artificial Intelligence Model for Detecting Tax Evasion Involving Complex Network Schemes Nuryani, Nuryani; Mutiara, Achmad Benny; Wiryana, I Made; Purnamasari, Detty; Putra, Souza Nurafrianto Windiartono
Aptisi Transactions On Technopreneurship (ATT) Vol 6 No 3 (2024): November
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v6i3.436

Abstract

Tax evasion through complex network schemes poses a significant challenge to tax authorities, leading to substantial revenue losses. This paper aims to develop and evaluate an artificial intelligence model designed to detect tax evasion within complex corporate networks, providing a comprehensive overview and prediction of tax avoidance behaviors. Employing a systematic literature review and document analysis of applicable tax regulations, the study utilizes Social Network Analysis (SNA) as a primary technique for mapping and analyzing taxpayer networks. The process involves matching taxable identities, constructing taxpayer graphs, extracting features, and developing a machine learning model. The proposed architectures and processes demonstrate the potential for tax authorities to enhance their capabilities in detecting tax evasion involving complex networks, with the machine learning model effectively identifying features related to both individual and network characteristics of taxpayers. The findings suggest that the integration of artificial intelligence and big data analytics can significantly improve the detection of tax evasion in complex corporate structures, offering valuable tools for tax authorities to better enforce tax compliance.
Integrating Blockchain and AI in Business Operations to Enhance Transparency and Efficiency within Decentralized Ecosystems Rakhmansyah, Mohamad; Hadi, Muhammad Saiful; Junaedi, Sausan Raihana Putri; Ramahdan, Fikri Arsla; Putra, Souza Nurafrianto Windiartono
ADI Journal on Recent Innovation Vol. 6 No. 2 (2025): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v6i2.1177

Abstract

This study explores the integration of Blockchain and Artificial Intelligence (AI) technologies in business operations, aiming to enhance transparency and operational efficiency within decentralized ecosystems. Blockchain offers so- lutions to trust issues in business systems through its secure and transparent characteristics, while AI plays a pivotal role in data analysis and automating decision-making. This study uses a qualitative research approach, incorporat- ing case studies and expert interviews to examine the potential and challenges of applying these technologies. The results show that integrating Blockchain and AI accelerates business processes, reduces operational costs, and fosters trust among stakeholders in decentralized ecosystems. However, challenges such as technology adoption, scalability, and initial implementation costs remain signif- icant barriers. This research contributes to the development of more efficient and transparent operational strategies through the application of advanced tech- nologies, and provides a foundation for future research on the impact of these technologies in global business sectors.
Co-Authors Achmad Benny Mutiara Detty Purnamasari Hadi, Muhammad Saiful I Made Wiryana, I Made Junaedi, Sausan Raihana Putri Nuryani Nuryani Rakhmansyah, Mohamad Ramahdan, fikri Arsla