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All Journal Akurasi : Jurnal Studi Akuntansi dan Keuangan JOURNAL OF ECONOMICS EDUCATION AND ENTREPRENEURSHIP E-Jurnal Akuntansi
Irvan, Muhammad Alif Nur
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education

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How Accountability Shapes the Impact of Government Effectiveness on Corruption Outcomes Irvan, Muhammad Alif Nur; Amalia, Elsa
E-Jurnal Akuntansi Vol. 35 No. 8 (2025)
Publisher : Fakultas Ekonomi dan Bisnis Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/EJA.2025.v35.i08.p09

Abstract

This study aims to examine the effect of government effectiveness on corruption in ASEAN countries and to assess the moderating role of accountability in this relationship. Using a panel data covering the period 2013–2023, the study measures variables through the World Governance Indicators (WGI) and applies panel regression analysis. The findings show that government effectiveness has a significant negative effect on corruption, indicating that improved institutional capacity and public service delivery can effectively reduce corrupt practices. Furthermore, accountability positively moderates the relationship, suggesting that the impact of government effectiveness on corruption control is stronger in environments with greater public oversight and citizen engagement. These results support institutional theory and offer empirical evidence that successful anti-corruption reforms require the synergy of institutional strength and robust accountability mechanisms.
DOES OWNERSHIP MODERATE THE FINANCIAL PERFORMANCE AND CSR DISCLOSURE LINKAGE? Irvan, Muhammad Alif Nur; An Nurrahmawati; Elsa Amalia
Akurasi : Jurnal Studi Akuntansi dan Keuangan Vol 8 No 2 (2025): Akurasi: Jurnal Studi Akuntansi dan Keuangan, Desember 2025
Publisher : Faculty of Economics and Business University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/akurasi.v8i2.815

Abstract

This study examines the effect of financial performance on corporate social responsibility (CSR) disclosure by considering the moderating role of ownership structure, including institutional, family, foreign, and managerial ownership. The research is motivated by inconsistent empirical findings regarding the relationship between profitability and CSR disclosure in developing countries, particularly in controversial industries facing high legitimacy pressures. The sample consists of 102 firm-year observations of companies listed on the Indonesia Stock Exchange during the 2019–2023 period. The analysis employs Random-Effects Generalized Least Squares (GLS) panel regression with a lag-1 ROA as the k-test variable. The results reveal that Return on Assets (ROA) has a positive effect on CSR disclosure, consistent with legitimacy theory, which posits that sound financial performance enhances social transparency. However, managerial ownership weakens this relationship, whereas institutional, family, and foreign ownerships do not exhibit significant moderating effects. These findings underscore the importance of ownership characteristics in influencing CSR disclosure practices and provide implications for regulators and investors in strengthening corporate accountability, particularly in firms with dominant managerial ownership.
Fraud Detection Methods in Addressing Cyber Threats: A Systematic Literature Review in the Banking Sector Buchori, Willa Putri Malinda; Nirbita, Betanika Nila; Irvan, Muhammad Alif Nur; Husnaningtyas, Nadia; Ghina, Adila Durrotul
Journal of Economics Education and Entrepreneurship Vol 7, No 1 (2026): JEE, APRIL 2026
Publisher : Program Studi Pendidikan Ekonomi FKIP Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jee.v7i1.18299

Abstract

This research was conducted in order to determine the method of fraud detection. The method used in this research is Systematic Literature Review (SLR) with PRISMA Protocol. The steps taken include identification, screening, feasibility testing, and finalization of relevant studies from various leading databases such as Google Scholar, Scopus, Web of Science, Emerald, and IEEE Xplore. The results of the study identified eight main methods of fraud detection, namely big data analysis, machine learning algorithms, Natural Language Processing (NLP); Accounting Information Systems, Extremely Randomized Trees (ERT), rule-based systems, blockchain technology, Asexual Reproduction Optimization (ARO), Bayesian A/B testing, and authentication systems. These methods show varying degrees of effectiveness in detecting suspicious transactions and reducing the risk of digital fraud. The research findings not only discuss fraud detection methods, but also analyze the weaknesses and advantages of each method. The findings can be used as a practical reference source in preventing fraud by conducting fraud detection based on the right method.
Co-Authors Amalia, Elsa An Nurrahmawati Betanika Nila Nirbita Elsa Amalia Ghina, Adila Durrotul Nadia Husnaningtyas Willa Putri Malinda Buchori