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PENERAPAN ARTIFICIAL INTELLIGENCE (AI) DALAM PERAMALAN AKUNTANSI TINJAUAN LITERATUR DAN AGENDA PENELITIAN MASA DEPAN Pratama, Gilang Surya; Agus Munandar
Accounting Profession Journal (APAJI) Vol. 7 No. 1 (2025): Accounting Profession Journal (APAJI)
Publisher : Program Studi Akuntansi Fakultas Ekonomi dan Bisnis Universitas Kristen Indonesia Paulus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35593/apaji.v7i1.277

Abstract

This research examines recent developments in the application of Artificial Intelligence (AI) for accounting forecasting through a systematic review of literature published between 2020-2024. Using a systematic review methodology, this study analyzed 60 selected articles from Scopus, Web of Science, Science Direct and Google Scholar databases. The analysis results show significant improvements in forecasting accuracy using AI technology, with Machine Learning achieving 78% accuracy in revenue forecasting, Deep Learning 85% in financial trend prediction, and Natural Language Processing 89% in sentiment analysis. Major implementation challenges include data quality, infrastructure limitations, and data security. Development opportunities are identified in blockchain integration, hybrid models, and preprocessing automation. This research also identifies future research agendas that include the development of adaptive models and improved AI interpretability. The contribution of this research lies in providing a comprehensive understanding of the state-of-the-art application of AI in accounting forecasting and identifying future development directions.
Econometric panel data modeling of corporate carbon emission disclosure: Financial and environmental determinants in the mining industry Pratama, Gilang Surya; Gantino, Rilla
Journal of Advanced Sciences and Mathematics Education Vol. 6 No. 1 (2026): Journal of Advanced Sciences and Mathematics Education
Publisher : CV. FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/jasme.v6i1.1083

Abstract

Background: The growing urgency of climate change mitigation has intensified global attention on corporate transparency in carbon emission reporting. Companies operating in carbon-intensive industries, particularly the mining sector, face increasing pressure from regulators, investors, and the public to disclose environmental impacts in a systematic and accountable manner. However, empirical evidence explaining the determinants of corporate carbon emission disclosure remains limited, especially in emerging economies where sustainability reporting practices are still evolving. Aims: This study aims to develop an econometric panel data model to examine the influence of financial performance and environmental performance on corporate carbon emission disclosure, while also assessing the moderating role of firm size in strengthening disclosure behaviour. Methods: The research employs a quantitative approach using panel data econometric modelling. The dataset includes 40 mining companies listed on the Indonesia Stock Exchange during the period 2018–2024, generating 280 firm-year observations. Carbon emission disclosure is measured using a disclosure index, financial performance is proxied by return on equity, environmental performance is represented by the PROPER rating, and firm size is measured by the natural logarithm of total assets. The analysis applies a Fixed Effect Model with robust standard errors to control for unobserved firm heterogeneity. Result: The results show that financial performance and environmental performance significantly increase corporate carbon emission disclosure. In addition, firm size strengthens the relationship between environmental performance and disclosure intensity. Conclusion: The findings demonstrate that carbon disclosure is shaped by financial capability, environmental governance, and organizational scale. Firms with stronger financial capacity and better environmental performance tend to disclose carbon information more transparently, while larger firms respond more strongly to environmental accountability pressures. These results contribute to data-driven sustainability research and highlight the importance of strengthening environmental governance and transparent carbon reporting in emission-intensive industries