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All Journal Jurnal Equity International Journal of Digital Entrepreneurship and Business (IDEB) Equity
Maharani, Neni
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Economics, Econometrics & Finance Education Environmental Science Social Sciences Other

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Investigating The Effect of IFRS Implementation on Accounting Information Relevance Mulyadi, Nanda Pramayasti; Maharani, Neni; Valdiansyah, Riyan Harbi
International Journal of Digital Entrepreneurship and Business Vol 5 No 2 (2024): International Journal of Digital Entrepreneurship and Business (IDEB)
Publisher : Universitas Jakarta Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52238/ideb.v5i2.189

Abstract

The primary objective of this study is to evaluate the impact of International Financial Reporting Standards (IFRS) on the value of accounting information, as this metric serves as the predominant benchmark for a company's financial statements. This study employs a literature review methodology to compare pre- and post-IFRS implementation values in Indonesia against an understanding of accounting information value from existing companies. The findings of this study indicate that IFRS adoption does not significantly alter the value of accounting information in Indonesia. The implementation of IFRS principles is unlikely to induce substantial changes in countries such as Indonesia, which operates within a legal system that is unable to provide investors with adequate safeguards for secure investments. This situation is further exacerbated by the limited capacity of the legal function in these countries, particularly in the context of the predominant role of banks. The influence of global factors on the value of accounting information, particularly in Indonesia, further compounded these challenges.
Post-Covid-19 Financial Distress Analysis: Insights from Indonesian Transportation Sub-Sector Companies Maharani, Neni; Mulyadi, Nanda Pramayasti; Valdiansyah, Riyan Harbi
EQUITY Vol 28 No 1 (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.v28i1.10594

Abstract

The objective of this study is to analyze the prediction of financial distress in transportation sub-sector companies listed on the Indonesia Stock Exchange for the period 2021-2023 using four prediction models: Altman (Z-Score), Springate (S-Score), Zmijewski (X-Score), and Grover (G-Score). The study will calculate the level of accuracy. The analysis utilizes secondary data, specifically financial reports from 12 companies, constituting a total sample of 36. The findings indicate that the Zmijewski and Grover model exhibits the highest accuracy rate of 76%, followed by zmijewski with 71%, springate with 46%, and Altman with 26%. These results suggest that the Zmijewski and Grover model is appropriate model for use in the transportation sub-sector in Indonesia during the observed period. The implications of this research suggest that Zmijewski and Grover's model can be utilized by companies to evaluate financial conditions proactively, by investors to assess investment risks, and by regulators to ensure the stability of the transportation sub-sector. However, this study also underscores that Zmijewski and Grover's model cannot be generalized to all sectors, emphasizing the necessity for further research to test the model in other sectors by considering both financial and non-financial variables. Keywords: Financial Distress; Accuracy; Post-covid; DAR; Net Profit.
Post-Covid-19 Financial Distress Analysis: Insights from Indonesian Transportation Sub-Sector Companies Maharani, Neni; Mulyadi, Nanda Pramayasti; Valdiansyah, Riyan Harbi
EQUITY Vol 28 No 1 (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.v28i1.10594

Abstract

The objective of this study is to analyze the prediction of financial distress in transportation sub-sector companies listed on the Indonesia Stock Exchange for the period 2021-2023 using four prediction models: Altman (Z-Score), Springate (S-Score), Zmijewski (X-Score), and Grover (G-Score). The study will calculate the level of accuracy. The analysis utilizes secondary data, specifically financial reports from 12 companies, constituting a total sample of 36. The findings indicate that the Zmijewski and Grover model exhibits the highest accuracy rate of 76%, followed by zmijewski with 71%, springate with 46%, and Altman with 26%. These results suggest that the Zmijewski and Grover model is appropriate model for use in the transportation sub-sector in Indonesia during the observed period. The implications of this research suggest that Zmijewski and Grover's model can be utilized by companies to evaluate financial conditions proactively, by investors to assess investment risks, and by regulators to ensure the stability of the transportation sub-sector. However, this study also underscores that Zmijewski and Grover's model cannot be generalized to all sectors, emphasizing the necessity for further research to test the model in other sectors by considering both financial and non-financial variables. Keywords: Financial Distress; Accuracy; Post-covid; DAR; Net Profit.
Co-Authors Mulyadi, Nanda Pramayasti Riyan Harbi Valdiansyah