Sarah Zettira Agam Darwis
Universitas Muhammadiyah Makassar

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Application of Cloud Computing in Modern Accounting Practices a Systematic Literature Review Sarah Zettira Agam Darwis; Muchriana Muchran; Muh Ramly
Harmoni Economics: International Journal of Economics and Accounting Vol. 3 No. 1 (2026): Harmoni Economics: International Journal of Economics and Accounting
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/harmonieconomics.v3i1.460

Abstract

This study explores the application of cloud computing in modern accounting practices through a systematic literature review. The rapid advancements in information technology have revolutionized accounting information systems, making processes more efficient, integrated, and responsive. Cloud computing allows real-time, remote access to financial data across devices, enhancing transaction processing, reporting, and overall accuracy. The reviewed literature highlights that cloud-based accounting improves operational efficiency by automating tasks, streamlining workflows, enabling cross-department collaboration, and reducing infrastructure and maintenance costs. It also leads to better financial data quality through continuous updates, standardized procedures, and improved audit trails. Strategically, cloud adoption strengthens accounting’s role as a business partner by providing faster, more relevant insights for planning, control, and performance evaluation. However, challenges persist, particularly regarding data security, privacy risks, regulatory compliance, and service disruptions. Additionally, human resource factors, such as digital skills, change management, and user acceptance, are critical to successful implementation. In conclusion, this study provides a conceptual overview of how cloud computing enhances modern accounting, emphasizing its benefits in improving efficiency and decision-making, while recognizing the challenges that need to be addressed for its sustainable adoption.
A Comparative Analysis of Cost Efficiency and Profitability in Banking: A Study of Conventional and Digital Banks in Indonesia Sarah Zettira Agam Darwis; Muh Risnandar; Idil Rakhmat Susanto
Ilmu Ekonomi Manajemen dan Akuntansi Vol. 7 No. 1 (2026): Jurnal Ilmu Ekonomi Manajemen dan Akuntansi
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/ileka.v7i1.3625

Abstract

The banking sector's business model has changed due to digital transformation, which has also driven the emergence of digital banks as a more adaptive option for financial services. However, there are still differences of opinion regarding the success of digital banks' business models compared to large-scale traditional banks, especially in terms of profitability and operational efficiency. The purpose of this study is to compare the operational cost efficiency and profitability of digital banks and traditional banks in the KBMI 4 category listed on the Indonesia Stock Exchange for the years 2023–2025. Using secondary data from the annual financial reports of eight sample banks, this study employed a comparative quantitative methodology. Descriptive statistics, homogeneity tests, normality tests, and Independent Samples t-tests were used in the analysis. Return on Assets (ROA) showed no significant difference, while Operating Expenses to Operating Income (BOPO), Cost to Income Ratio (CIR), and Net Interest Margin (NIM) did show significant differences. Although digital banks generate higher interest margins, conventional banks have superior operational efficiency (KBMI 4). However, because technology investments are expensive, these benefits do not fully improve profitability. This study contributes to empirical data on the digital transformation of Indonesian banking and shows that the ability to manage resources and leverage economies of scale, in addition to digitalization, determines competitive advantage. To obtain a more complete picture, it is recommended that future studies use larger sample sizes, observation durations, and better analytical techniques.