Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Asia Pacific Fraud Journal SASI
Baroto, Wishnu Agung
Unknown Affiliation
Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Advancing Digital Forensic through Machine Learning: An Integrated Framework for Fraud Investigation Baroto, Wishnu Agung
Asia Pacific Fraud Journal Vol. 9 No. 1: 1st Edition (January-June 2024)
Publisher : Association of Certified Fraud Examiners Indonesia Chapter

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21532/apfjournal.v9i1.346

Abstract

The rise of cybercrime and cyber-related crime encourages efficient digital forensic investigations more crucial than ever before. Traditional investigation methods can be time-consuming, costly, and resource-intensive, while machine learning algorithms have the potential to reduce the complexity by promoting automation and investigation capabilities. This study begins with an analysis of digital forensics framework using a document analysis methodology. Moreover, exploring current practice and potential implementation of machine learning in digital forensics for fraud investigation is demonstrated through the features of Autopsy 4.15.0, a widely known digital forensics tool. The findings suggest the implementation of a comprehensive digital forensic framework that prioritizes the interpretation phase, with the support of machine learning capabilities. At present, machine learning mainly supports the analysis phase, which happens to be the most time-intensive process of digital forensic investigations. Furthermore, as fraud investigation has a role of fraud detection and prevention, current digital forensics procedures do not support the fraud detection and prevention process, despite the potential for machine learning to support this through pattern recognition.These discoveries are particularly significant in the fight against fraudulent activities, such as tax fraud, data fraud, financial fraud, and asset misappropriation, in the digital age.
Advancing Digital Forensic through Machine Learning: An Integrated Framework for Fraud Investigation Baroto, Wishnu Agung
Asia Pacific Fraud Journal Vol. 9 No. 1: 1st Edition (January-June 2024)
Publisher : Association of Certified Fraud Examiners Indonesia Chapter

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21532/apfjournal.v9i1.346

Abstract

The rise of cybercrime and cyber-related crime encourages efficient digital forensic investigations more crucial than ever before. Traditional investigation methods can be time-consuming, costly, and resource-intensive, while machine learning algorithms have the potential to reduce the complexity by promoting automation and investigation capabilities. This study begins with an analysis of digital forensics framework using a document analysis methodology. Moreover, exploring current practice and potential implementation of machine learning in digital forensics for fraud investigation is demonstrated through the features of Autopsy 4.15.0, a widely known digital forensics tool. The findings suggest the implementation of a comprehensive digital forensic framework that prioritizes the interpretation phase, with the support of machine learning capabilities. At present, machine learning mainly supports the analysis phase, which happens to be the most time-intensive process of digital forensic investigations. Furthermore, as fraud investigation has a role of fraud detection and prevention, current digital forensics procedures do not support the fraud detection and prevention process, despite the potential for machine learning to support this through pattern recognition.These discoveries are particularly significant in the fight against fraudulent activities, such as tax fraud, data fraud, financial fraud, and asset misappropriation, in the digital age.
Restorative Justice Arrangements in Civil Law, Common Law, and Indonesian Legal Systems Apituley, Lilian Gressthy Florencya; Baroto, Wishnu Agung; Soplantila, Valentino Dinatra
SASI Volume 31 Issue 4, December 2025
Publisher : Faculty of Law, Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47268/sasi.v31i4.3270

Abstract

Introduction: This article will outline how the application of restorative justice in the civil law system, the common law system, and the Indonesian legal system compares.Purposes of the Research: This study aims to provide a comprehensive comparison of the regulation and implementation of restorative justice across three legal systems - civil law, common law, and Indonesia’s hybrid legal system - and to identify best practices and challenges that can inform the development of restorative justice in diverse legal contexts.Methods of the Research: The study uses a normative legal method, combining a legal concept approach to examine the philosophical and ethical foundations of restorative justice with a statutory approach to analyze formal legal mechanisms. This methodology links legal theory with practice while highlighting the integration of normative principles within Indonesia’s socio-cultural context, including Pancasila and customary law.Results of the Research: This study compares restorative justice implementation in civil law, common law, and Indonesia’s legal system. Civil law is rigid and procedural, while common law allows flexible mechanisms such as victim–offender mediation. In Indonesia, despite Supreme Court Rule Number 1 of 2024, challenges include limited understanding among law enforcement, inconsistent application, and insufficient institutional support. Strengthening implementation requires harmonized regulations, professional training, community-based mechanisms rooted in local wisdom and customary law, and public awareness. Indonesia’s model highlights a transformative approach that integrates restorative principles with national values of humanity, justice, and social harmony.
Co-Authors Apituley, Lilian Gressthy Florencya Soplantila, Valentino Dinatra