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All Journal Jurnal Ilmiah Edunomika (JIE) JSMA (Jurnal Sains Manajemen dan Akuntansi) Journal of Economics and Business Letters Jurnal Ekonomi Perjuangan (JUMPER) RESLAJ: Religion Education Social Laa Roiba Journal
Rendi Kusuma Natita
Universitas Jenderal Achmad Yani
Religion Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Social Sciences

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Pengaruh Kompetensi Auditor erhadap Kualitas Audit (Survey Pada Auditor yang Lulus Kuliah Ketika Masa Pandemik Covid-19 dan Bekerja di Kantor Akuntan Publik Berafiliasi Internasional) Rendi Kusuma Natita; Ali Rahman Reza Saputra; Intan Pramesti Dewi
JSMA Vol 15 No 2 (2023): JSMA (Jurnal Sains Manajemen dan Akuntansi)
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi STAN IM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37151/jsma.v15i2.152

Abstract

Penelitian ini berupaya untuk mengetahui bagaimana Kompetensi Auditor mempengaruhi Kualitas Audit dan bagaimana Kualitas Audit dan Kompetensi berinteraksi. Populasinya adalah auditor dari perusahaan akuntan publik yang terkait atau berkolaborasi di seluruh dunia. Dengan menggunakan data primer yang bersumber dari kuesioner yang diajukan kepada respnden. Sementara sampel untuk diperoleh dengan menggunakan metode judgement sampling. Dengan data yang diolah sebanyak 80 data. Dihitung dengan menggunakan skala ukur ordinal dengan metode Skala Likert. Penelitian ini menujukkan hasil bahwa dan kompetensi audit secara simultan atau bersamasama berpengaruh signifikan secara positif terhadap Kompetensi audit.
PENGARUH TAX AMNESTY DAN TARIF PAJAK TERHADAP KEPATUHAN WAJIB PAJAK Bani Binekas; Rendi Kusuma Natita
JURNAL ILMIAH EDUNOMIKA Vol 8, No 3 (2024): EDUNOMIKA
Publisher : ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/jie.v8i3.14100

Abstract

This study measures the influence of tax amnesty and tax rates on taxpayer compliance with the aim of providing further understanding to those implementing tax amnesty programs and setting tax rates. The indicators used to measure taxpayer compliance include timely submission of tax returns; no tax arrears for any type of tax, except for tax arrears that have been approved for installment payments or deferred tax payments; financial statements audited by a public accountant or government financial supervisory agency with an unqualified opinion for three consecutive years; and no convictions for tax-related crimes based on a final court decision within the last five years. The indicators for tax amnesty include taxpayer knowledge of the tax amnesty program, taxpayer understanding of the tax amnesty program, taxpayer awareness of the tax amnesty, and the benefits of the tax amnesty program for taxpayers. The indicators for the tax rate variable include proportional rates, fixed rates, progressive rates, and regressive rates. This research aims to test hypotheses, typically explaining the nature of certain relationships or determining the independence of two or more factors in a situation. This study employs an explanatory method, wherein the researcher seeks to identify the causes of one or more issues. The results of the study indicate that taxpayer compliance is influenced by tax amnesty.
Pengaruh Metode Springate dalam Memprediksi Financial Distress pada Perusahaan Konstruksi yang Terdaftar di Bursa Efek Indonesia (BEI) Periode 2021-2024 Silmi Azhaar Istiqomah; Rendi Kusuma Natita
Reslaj: Religion Education Social Laa Roiba Journal Vol. 8 No. 5 (2026): RESLAJ: Religion Education Social Laa Roiba Journal
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/reslaj.v8i5.11705

Abstract

This study aims to analyxe the effect of Working Capital to Total Assets, Earning Before Interest and Taxes to Total Assets, Earning Before Taxes to Current Liabilities, and Sales to Total Assets on Financial Distress, as measured using the Springate model, in construction companies listed on the Indonesia Stock Exchange for the 2021-2024 period. This study uses a quantitative approach with multiple linear regression methods on 32 obrervations selected through puroosive sampling. The data used are secondary data in the form of audited annual financial reports, The results show that all independent variables have a significance level below 0,05. The variable Earning Before Taxes to Current Liabilities is proven to be the most dominant variable in influencing financial distress. The coefficient of determination value indicates that the model is able to adequately explain variations in financial distress. This finding indicates that financial ratios play an important role in detecting and predicting financial distress in conctruction companies.
The influence of Environmental, Social, Governance (ESG) and leverage on the cost of capital (empirical study on mining companies listed on the Indonesia Stock Exchange for the 2022-2024 period) Nia Yulianty; Rendi Kusuma Natita
Journal of Economics and Business Letters Vol. 6 No. 1 (2026): February 2026
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/jebl.v6i1.1592

Abstract

The primary objective of this investigation centers on evaluating the impact exerted by Environmental, Social, and Governance (ESG) factors together with leverage upon capital costs among mining corporations listed on the Indonesia Stock Exchange spanning the 2022–2024 interval. A quantitative methodology was employed, drawing upon secondary datasets sourced from audited annual reports, dedicated sustainability disclosures, and publicly available financial documentation. Through purposive sampling criteria, a cohort of 14 mining entities was delineated, yielding 42 firm-year observations for empirical scrutiny. ESG efficacy was quantified via a composite index aligned with Global Reporting Initiative (GRI) Disclosure Standards 2021, leverage was operationalized through the Debt-to-Equity Ratio (DER), and capital costs were proxied by the Weighted Average Cost of Capital (WACC). Rigorous preprocessing incorporated classical assumption validations, culminating in multiple linear regression analysis facilitated by IBM SPSS Statistics version 25. Empirical outcomes revealed that ESG disclosures manifest no discernible influence on capital costs, standing in stark juxtaposition to leverage, which demonstrated a negative and statistically robust association therewith. Collectively, ESG alongside leverage were found to significantly shape financing expenses, underscoring a synergistic explanatory mechanism. These results illuminate the preeminence of strategic debt management over sustainability signaling in modulating capital costs within Indonesia's mining landscape during the study window a nuance attributable to sectoral capital intensity and nascent ESG differentiation. By furnishing substantive evidence on the interplay of financial engineering and non-financial governance metrics, this inquiry enriches theoretical discourse on cost determinants within emerging market contexts, offering actionable insights for corporate treasurers navigating volatility-prone resource sectors.
ARTIFICIAL INTELLIGENCE DALAM PROSEDUR AUDIT SEBUAH SYSTEMATIC LITERATURE REVIEW Rendi Kusuma Natita; Rakhmat Siraz
JURNAL EKONOMI PERJUANGAN Vol. 7 No. 2 (2025): Jurnal Ekonomi Perjuangan (JUMPER)
Publisher : LP2M Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/jumper.v7i2.2509

Abstract

This study aims to examine the role of Artificial Intelligence (AI) in auditing procedures and evaluate its benefits and challenges. Using a Systematic Literature Review approach based on the PRISMA method, this research analyzes 14 relevant scientific articles published between 2014 and 2024. The findings indicate that AI has been widely applied across various stages of the audit process, including planning, internal control testing, substantive procedures, and reporting. Technologies such as Robotic Process Automation (RPA), Machine Learning (ML), Natural Language Processing (NLP), and Optical Character Recognition (OCR) have proven effective in improving audit efficiency, accuracy, and coverage by automating routine tasks and detecting anomalies in real time. However, the adoption of AI also faces challenges such as algorithm transparency limitations, data bias, privacy issues, and auditors’ limited understanding of the technology. The study concludes that the successful integration of AI into auditing depends heavily on auditor readiness, the development of transparent and accountable systems, as well as supportive regulations and ethical frameworks. This research is expected to contribute both academically and practically to the auditing profession in the era of digital transformation.
Co-Authors Ali Rahman Reza Saputra Bani Binekas Intan Pramesti Dewi Nia Yulianty Rakhmat Siraz Silmi Azhaar Istiqomah