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All Journal Jurnal Bisnis dan Akuntansi Lead Journal of Economy and Administration
Leonny Noviyana Sakti Pamungkas
Universitas Sebelas Maret
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences

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BIG DATA ADOPTION: HOW WILL IT IMPACT GOVERNMENT AUDIT QUALITY? Leonny Noviyana Sakti Pamungkas; Jaka Winarna; Y Anni Aryani
Jurnal Bisnis dan Akuntansi Vol. 26 No. 2 (2024): Jurnal Bisnis dan Akuntansi
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Sekolah Tinggi Ilmu Ekonomi Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34208/jba.v26i2.2493

Abstract

One of the problems and challenges in auditing is the large amount of data and complex problems. The existence of technology is currently a solution to simplify the audit process and improve audit quality. The problem is, not all auditors know the role of this technology. As a result, many still rely on manual methods that take a long time and are prone to errors. This research uses a System Literature Review (SLR) by collecting 61 articles and 6 international proceedings on data adoption in auditing in Scopus, Emerald, and SINTA. We also collected research articles conducted by Malakoute & Soumaya (2023) on audit quality factors as a simplification. We found that the impact factor of data adoption has some similarities to the audit quality factor in Malakoute & Soumaya (2023)) research. This finding indicates that Big Data can improve audit quality. In other words, if auditors apply Big Data in the audit process, it is likely that the audit results will be of high quality. This research provides an overview that can be used by auditors to consider data adoption in their implementation. If auditors apply Big Data in audits, the advantages of Big Data will affect audit quality in government. Keywords: Big Data adoption, SLR, Audit Quality, Audit Success
Mutual Fund Volatility in Election Years: Low Risk or High Risk? Riedwan Adhie Saputra; Leonny Noviyana Sakti Pamungkas; Setyaningtyas Honggowati
Lead Journal of Economy and Administration Vol 3 No 4 (2025): Lead Journal of Economy and Administration (LEJEA)
Publisher : International Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56403/lejea.v3i4.273

Abstract

This research aims to analyze the patterns of price fluctuations in mutual funds over a specific time frame, particularly in relation to political events such as national elections. The primary objective is to evaluate the risk levels of mutual funds in countries undergoing election cycles, which are often associated with heightened economic and political uncertainty. To achieve this, the study employs Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized ARCH (GARCH) models—two widely recognized econometric tools for analyzing time series data exhibiting volatility clustering. These models enable the classification and comparison of both low and high volatility conditions in mutual fund performance. The dataset comprises mutual fund data from 10 different countries, covering the period between 2019 and 2024. Each selected country has a mature mutual fund market with a focus on equity (stocks) and fixed-income (bonds) instruments. The findings reveal distinct variations in volatility levels among the countries studied, influenced by their respective political climates during election periods. The application of ARCH and GARCH modeling proves effective in capturing these fluctuations. The results offer valuable insights for investors seeking to minimize risk by diversifying their portfolios across more stable mutual funds, especially during times of political transition. This research contributes to better-informed investment decision-making in politically dynamic environments.
Co-Authors JAKA WINARNA Riedwan Adhie Saputra Setyaningtyas Honggowati Y Anni Aryani