Jurnal Akuntansi dan Governance

Pengaruh Sistem Pengendalian Intern Pemerintah (SPIP) dan Aksesibilitas Laporan Keuangan terhadap Akuntabilitas Pengelolaan Keuangan Desa

2025-03-27T22:22:45+00:00

Objectives: To determine and analyze the effect of the Government Internal Control System (SPIP) and the Accessibility of Financial Reports on the Accountability of Village Financial Management in the Village Government in Muara Badak District.

Design/method/approach: The type and source of data in this research is quantitative using primary data. The sampling technique used was purposive sampling, with a total sample of 91 respondents consisting of village government officials and BPD in 13 villages in Muara Badak District. This research uses data analysis techniques conducted with Structural Equation Modeling - Partial Least Square (SEM-PLS) using the SMART-PLS Ver 4.0 program.

Results/findings: The government internal control system (SPIP) has a significant positive effect on the accountability of village financial management and the accessibility of financial reports has no significant positive effect on the accountability of village financial management.

Theoretical contribution: The results of this study can be useful for further researchers and can be used as reference material, as well as add and develop knowledge, especially in the field of public sector accounting.

Practical contribution: As additional insight for village financial managers to consider and pay attention to the importance of the government internal control system and the accessibility of financial reports to increase the value of village financial management accountability.

Limitations: Small population and sample of only 13 villages. Limited discussion of accessibility to the accessibility of financial reports (accountability) only.

Keywords: Government Internal Control System (SPIP), Accessibility of Financial Reports, Accountability of Village Financial Management.

Model Pengukuran Risiko Operasional Perusahaan Asuransi Syariah Menggunakan Metode Analytical Network Process

2025-03-28T15:42:55+00:00

Model pengukuran risiko operasional, yang pada umumnya menggunakan pendekatan kuantitatif, dinilai tidak mampu menangkap seluruh aspek yang diperlukan untuk membangun model pengukuran yang memadai. Penelitian ini bertujuan merancang model pengukuran risiko operasional yang lebih komprehensif dengan mempertimbangkan berbagai faktor, seperti faktor risiko, aktor, data kejadian kerugian, serta alternatif strategi mitigasi risiko yang tepat untuk perusahaan asuransi umum syariah.

Penelitian ini menggunakan pendekatan kualitatif berdasarkan pendapat para ahli menggunakan metode Analytical Network Process (ANP), menghasilkan model pengukuran risiko operasional yang lebih handal dan memberikan kontribusi penting bagi industri. Temuan penelitian menunjukkan bahwa prioritas strategi mitigasi risiko operasional berdasarkan ANP adalah peningkatan kualitas standar pencatatan semua risiko dengan sistem informasi yang terintegrasi.

Dapatkah Penghasilan Komprehensif Lainnya Digunakan sebagai Media Tindakan Kecurangan Laporan Keuangan?

2025-01-31T08:33:55+00:00

Objectives: This study aims to prove that Others Comprehensive Income (OCI) fair value hierarchy and presentation of plans realize fraudulent financial statement.

Design/method/approach: The data observed are 1,890 companies listed on the IDX for all industrial sectors for the period 2021-2023. Hypothesis were tested with multiple linear regression analysis.

Results/findings: We found that OCI level 3 has a significant positive effect on the fraudulent financial reporting proxied by Beneish M Score. While OCI Reclassification has a significant negative effect on the Beneish M Score.

Theoretical contribution: The low quality of fair value input or the high subjectivity of management can be a medium for financial reporting fraud, but accounting standard regulations regarding the submission of unrealized earnings plans for the current period have been proven to be able to reduce the potential for fraud.

Practical contribution: The actuarial profession in determining the fair value of level 3 input must be based on professional considerations, not on management orders.

Limitations: OCI is only classified based on the fair value hierarchy and reclassification, even though it can also be based on the presence or absence of final tax burdens, which are relevant to fraud through tax avoidance

Analisis Faktor-Faktor yang Mempengaruhi Peringkat Sukuk di Indonesia

2025-01-31T08:35:41+00:00

Objectives: This study aims to analyze the factors that affect the ranking of sukuk. This analysis is useful for optimizing sukuk investment decision-making.

Design/method/approach: This quantitative research uses data from the annual reports of companies with sukuk and sukuk rating reports. The sample is 90 sukuk companies listed on the Indonesia Stock Exchange and still outstanding during the 2021-2023 period, so 270 data were obtained. The data were analyzed with panel data regression analysis on SPSS software.

Results/findings: The results show that the size of the board of commissioners and sukuk type have a positive influence on the sukuk rating, the leverage variable has a negative influence on the sukuk rating. Variables that have no influence on the sukuk rating are the number of audit committees and asset growth.

Theoretical contribution: The findings of this research can improve the understanding in the field of financial accounting and become a reference for conducting further research on sukuk rating.

Practice/policy contribution: This study offers investors guidance on the key factors influencing sukuk ratings, which serve as a basis for sukuk investment.

Limitations: The years observed in this study are limited from 2021 to 2023. In addition, the research object only focuses on the sukuk of companies listed on the Indonesia Stock Exchange

Peran Artificial Intelligence dalam Meningkatkan Kualitas Audit: Tinjauan Literatur Sistematis

2025-01-31T08:36:53+00:00

Objectives: This study aims to explore the role of AI in improving audit quality.

Design/method/approach: This study used the Systematic Literature Review (SLR) method to explore the use of AI in auditing. The object of this study was scholarly articles published between 2018-2023. The articles covered the use of AI to optimize the efficiency, accuracy and reliability of the audit process.

Results/findings: The results showed that AI is able to automate routine tasks, detect fraud, and identify risks more quickly and accurately than traditional methods. Technologies such as blockchain, machine learning, and advanced data analytics contribute significantly to data-driven decision-making, which improves the overall quality of audits.

Theoretical contribution: This research contributes to the literature by expanding the understanding of how AI technologies can improve audit quality

Practical contribution: This research provides practical guidance for auditors and companies to optimally utilize AI technologies

Limitations: This study relies on secondary literature and potential bias in data interpretation, so future research is recommended to explore the empirical impact of AI implementation on audits in different sectors.

Evaluasi Metode Deteksi Financial Distress pada Perusahaan LQ45

2025-01-31T08:37:57+00:00

Objectives: This study aims to evaluate the accuracy of three financial distress prediction models (Springate, Zmijewski, Grover) on LQ45 companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2023 period. The focus is to assess the models' effectiveness in addressing contemporary financial challenges such as debt restructuring and financial distress indicators amidst dynamic global economic conditions.

Design/method/approach: This quantitative research utilizes secondary data from 37 LQ45 companies selected through purposive sampling, resulting in 148 financial statements for the 2020–2023 observation period. The analysis employs financial ratios and prediction scores from each model using Microsoft Excel for computation.

Results/findings: The Grover model demonstrates the highest accuracy rate (95%) with a type error of 6%, outperforming Zmijewski (accuracy 89%, type error 11%) and Springate (accuracy 59%, type error 41%). This suggests that the Grover model is superior in detecting financial distress.

Theoretical contribution: This study identifies the Grover model as the most accurate method for predicting financial distress in Indonesia. It contributes to the development of more relevant financial distress prediction models for the capital market.

Practical contribution: The findings provide critical insights for shareholders and stakeholders to detect financial risks in LQ45 companies.

Limitations: The study is limited by its reliance on classical prediction models, focus on LQ45 companies, and analysis restricted to the 2020–2023 period. Modern approaches like machine learning, which could enhance prediction accuracy, are not explored.

Type: empirical, review (conceptual and viewpoints).