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All Journal Jurnal Pengabdian kepada Masyarakat Nusantara Mattawang: Jurnal Pengabdian Masyarakat Indonesian Management and Accounting Research Jurnal Akuntansi Trisakti Ekonomi Digital Journal of Artificial Intelligence and Digital Business TOFEDU: The Future of Education Journal Dirkantara Indonesia El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam IPSSJ Equity JIMEK
Amalina, Nurhafifah
Universitas Trisakti
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Artificial Intelligence and Sustainability Reporting: Performance Outcomes in ESG Investing Lin Oktris; Siti Fathimah Azzahra; Nengzih Nengzih; Nurhafifah Amalina; Maisarah Mohamed Saat
EQUITY Vol 28 No 2 (2025): EQUITY
Publisher : Department of Accounting, Faculty of Economics and Business, Universitas Pembangunan Nasional Veteran Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34209/equ.v28i2.13063

Abstract

The convergence of artificial intelligence and sustainable finance represents a fundamental transformation in investment decision-making, yet empirical evidence concerning effectiveness remains fragmented across diverse research domains. This study synthesises evidence from 43 peer-reviewed investigations spanning 2020 to 2024, examining artificial intelligence applications in environmental, social, and governance investing through systematic meta-analysis following PRISMA 2020 guidelines. Random-effects models demonstrate that artificial intelligence technologies significantly enhance risk-adjusted financial returns (standardised mean difference = 0.58; 95% confidence interval: 0.44-0.72; p<0.001), translating to approximately 5.2 per cent annual performance improvement, and environmental, social, and governance prediction accuracy (standardised mean difference = 0.53; 95% confidence interval: 0.38-0.68; p<0.001), representing 15 per cent error reduction compared with traditional methodologies. Ensemble machine learning demonstrates robust performance (standardised mean difference = 0.64; I²=45 per cent), whilst deep learning exhibits highest effects with substantial variability (standardised mean difference = 0.71; I²=68 per cent). Implementation success depends critically on data quality infrastructure (identified in 88 per cent of studies) and phased deployment strategies (effective in 64 per cent of cases). Moderate evidence certainty supports that artificial intelligence represents genuine capability advancement, though unexplained heterogeneity (I²=58-62 per cent) limits precise outcome prediction in specific contexts. Findings provide evidence-based guidance for investment managers adopting artificial intelligence technologies, policymakers developing regulatory frameworks, and researchers identifying future research priorities. Keywords: artificial intelligence; sustainable finance; ESG investing; meta-analysis; machine learning; investment decision-making; financial technology
Pengaruh Pengalaman Kerja, Skeptisme Profesional, Indepedensi, Tekanan Waktu dan Beban Kerja Auditor dalam Mendeteksi Kecurangan : Studi Empiris Akuntan Publik Kota Jakarta Rahmah Raminda; Agus Bagus Budi N; Nurhafifah Amalina
Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Vol. 5 No. 3 (2025): November: Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan (JIMEK)
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jimek.v5i3.8009

Abstract

This study aims to examine and analyze the influence of several individual and situational factors on the auditor’s ability to detect fraud, which is an essential competence in maintaining the integrity of financial reporting. The variables observed in this research include work experience, professional skepticism, independence, time pressure, and workload. The study was conducted in Jakarta and involved auditors working at Public Accounting Firms (KAP) across the city. Using a quantitative approach, the research employed a survey method with a total sample of 240 auditors who were selected as respondents. Data were collected through structured questionnaires and then analyzed using multiple linear regression, with statistical processing carried out using SPSS version 26. The findings of this study indicate that four variables—work experience, professional skepticism, independence, and time pressure—have a positive and significant influence on the auditor’s ability to detect fraud. This suggests that auditors who possess greater professional experience, a high level of skepticism, and strong independence are more capable of identifying fraud, even under conditions of time pressure. Interestingly, time pressure, which is often considered a constraint in auditing, was found to enhance fraud detection ability, possibly because it drives auditors to focus and prioritize critical aspects of their tasks. In contrast, the workload variable did not show a significant impact, indicating that the number of tasks or assignments alone may not reduce or improve an auditor’s effectiveness in detecting fraud. Overall, the study contributes to the understanding of the factors that shape auditors’ effectiveness in detecting fraudulent activities. The results emphasize the importance of enhancing auditor competence through continuous training and professional development, fostering independence in decision-making, and maintaining an optimal balance in task allocation.
Co-Authors Agus Bagus Budi N Brina Sitanggang De Gala Christo Randzio Simbolon Dewi, R. Rosiyana Dimas Saukas Pribadi Fabiola, Livia Fatik Rahayu Firda Amelia Ice Nasyrah Noor Idrianita Anis Joysinta, Angel Calista Lin Oktris Maisarah Mohamed Saat Marwah, Fadillah Nengzih Nengzih Patrisia Patrisia Retnagafia Manao Pryobudi Purbosanjoyo Putri Ramadhani Rahmah Raminda Rina Hartanti Rindi Ayu Ristiani Sakinah, Machdiah Seto Makmur Siti Fathimah Azzahra Wahyuni, Lidia Wien Alfatah Winda Pretty Handayani Sihombing Windhy Puspitasari Yanti, Harti Budi