Published: 2024-06-01
Peran Big Data Analytics dan Kualitas Audit dalam Memperkuat Kemampuan Auditor Mendeteksi Kecurangan Laporan Keuangan
DOI: 10.35870/jemsi.v10i3.2350
Deswari Ayu Putri, Abu Nizarudin, Julia
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Deswari Ayu Putri:
University of Bangka Belitung
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Abu Nizarudin:
University of Bangka Belitung
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Julia:
University of Bangka Belitung
Abstract
Penelitian ini bertujuan untuk menganalisis pengaruh big data analytics terhadap kualitas audit serta dampaknya pada kemampuan auditor dalam mendeteksi kecurangan laporan keuangan. Kualitas audit dalam penelitian berperan sebagai variabel mediasi atau intervening. Penelitian ini merupakan jenis penelitian kuantitatif deskriptif dan asosiatif dengan menggunakan metode survei melalui penyebaran kuesioner dalam pengumpulan datanya. Adapun responden dalam penelitian ini adalah 51 (lima puluh satu) pemeriksa di Badan Pemeriksa Keuangan Perwakilan Provinsi Bangka Belitung. Pengujian statistik dalam penelitian ini berupa structural equation modelling (SEM) dengan bantuan aplikasi SmartPLS versi keempat. Hasil dari penelitian ini menunjukkan bahwa big data analytics berpengaruh terhadap kualitas audit, tetapi tidak dengan pendeteksian kecurangan. Kualitas audit pun terbukti berpengaruh terhadap pendeteksian kecurangan, namun belum mampu memediasi hubungan big data analytics terhadap kemampuan auditor dalam mendeteksi kecurangan laporan keuangan.
Keywords
Article Information
This article has been peer-reviewed and published in the JEMSI (Jurnal Ekonomi, Manajemen, dan Akuntansi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 10 No. 3 (2024)
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Section: Articles
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Published: 2024-06-01
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License: CC BY 4.0
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Copyright: © 2024 Authors
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DOI: 10.35870/jemsi.v10i3.2350
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No author biographies available.
-
Anissa, A. I. N. A., & Novita, N. (2023). Penggunaan Data Analytics Terhadap Peningkatan Deteksi Kecurangan Pada Pemeriksaan Eksternal. Journal of Economic, Management, Accounting, and Tcehnology (JEMATech), 6(1), 34–45. https://doi.org/https://doi.org/10.32500/jematech.v6i1.3435
-
Association of Certified Fraud Examiners (ACFE). (2022). Occupational Fraud 2022: A Report to the nations. Association of Certified Fraud Examiners, 1–96.
-
Bendickson, J., Muldoon, J., Liguori, E., & Davis, P. E. (2016). Agency theory: the times are changing. Management Decision, 54(1), 174–193. https://doi.org/DOI 10.1108/MD-02-2015-0058
-
BPK RI. (2018). Menelisik Cara Kerja BPK dalam Memeriksa Keuangan Negara. BPK Perwakilan Provinsi Sulawesi Selatan. https://sulsel.bpk.go.id/menelisik-cara-kerja-bpk-dalam-memeriksa-keuangan-negara/
-
BPK RI. (2021). BPK GELAR WORKSHOP PENGGUNAAN BIG DATA ANALYTICS (BIDICS). BPK Republik Indonesia. https://www.bpk.go.id/news/bpk-gelar-workshop-penggunaan-big-data-analytics-bidics
-
BPK RI. (2022). DUGAAN TINDAK PIDANA KORUPSI DANA APBD OLEH BENDAHARA DINAS KESEHATAN PROVINSI KEPULAUAN BANGKA BELITUNG. BPK PERWAKILAN PROVINSI KEPULAUAN BANGKA BELITUNG. https://babel.bpk.go.id/dugaan-tindak-pidana-korupsi-dana-apbd-oleh-bendahara-dinas-kesehatan-provinsi-kepulauan-bangka-belitung/
-
Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. ResearchGate, 295–336.
-
Claudiastuti, M. A. (2023). Pengaruh Mitigasi Akuntansi Forensik Dan Integrasi Teknologi Big Data Terhadap Deteksi Kecurangan Internal. Jurnal Ekonomi Trisakti, 3(2), 3415–3424. https://doi.org/10.25105/jet.v3i2.18132
-
Ginting, R. (2022). Analisis Big Data (R. Firmansyah & Y. D. Kristanto (eds.)). Lakeisha.
-
Hair, J. F., Hult, T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook. In Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705511.2022.2108813
-
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
-
Hartono, J. (2019). Kajian Topik-Topik Mutakhir dan Agenda Riset ke Depan (1st ed.) (Edisi Pert). Andi.
-
Jensen, M. C., & Meckling, W. H. (1976). THEORY OF THE FIRM: MANAGERIAL BEHAVIOR, AGENCY COSTS AND OWNERSHIP STRUCTURE. Journal of Financial Economics, 3(4), 305–360. https://doi.org/https://doi.org/10.1016/0304-405X(76)90026-X
-
Kompas. (2023, April 10). Berbagai Kasus “Fraud” Membahayakan Ekonomi Indonesia. Kompas.Com. https://money.kompas.com/read/2023/04/10/140841526/berbagai-kasus-fraud-membahayakan-ekonomi-indonesia?page=all
-
Listya, A., Aspahani, & Sitepu, C. D. S. (2023). Implementasi Big Data Analytics dan Opini Audit terhadap Kualitas Audit : Audit Delay Sebagai Variabel Mediasi. Owner: Riset Dan Jurnal Akuntansi, 7(3), 2062–2071. https://doi.org/10.33395/owner.v7i3.1531
-
Mahkamah Konstitusi Republik Indonesia. (2022, February 9). APBN dan APBD Memiliki Kesatuan Arah Anggaran untuk Kemakmuran Rakyat. Mahkamah Konstitusi Republik Indonesia. https://www.mkri.id/index.php?page=web.Berita&id=17987&menu=2
-
Meitasari, R. C., & Manurung, E. T. (2023). Perceived Ease of Use and Usefulness of Big Data to Audit Quality. Proceeding of International Conference on Accounting and Finance, 1, 123–128. https://doi.org/10.20885/InCAF.vol1.art14
-
Putra, N. S., Ritchi, H., & Alfian, A. (2023). Hubungan Big Data Analytics terhadap Kualitas Audit: Penerapan pada Instansi Pemerintah. Jurnal Riset Akuntansi Dan Keuangan, 11(1), 57–72. https://doi.org/10.17509/jrak.v11i1.55139
-
Putra, W. E., Kusuma, I. L., & Dewi, M. W. (2021). MODEL HUBUNGAN KOMPETENSI, INDEPENDENSI, PROFESIONALISME DAN KUALITAS AUDIT SERTA DAMPAKNYA TERHADAP KEMAMPUAN MENDETEKSI FRAUDS. Jurnal Akuntansi Dan Pajak, 22(2), 1–14. https://doi.org/10.29040/jap.v22i2.3517
-
Putri, A. M. H. (2023, April 18). Kacau! Bupati Mendominasi Deretan Pejabat yang Kena OTT 2023. CNBC Indonesia. https://www.cnbcindonesia.com/research/20230417203652-128-430765/kacau-bupati-mendominasi-deretan-pejabat-yang-kena-ott-2023
-
Riyanti, E. C., W Putri, H. C., Artadi, W., & Umar, H. (2019). PENGARUH KUALITAS AUDIT TERHADAP FRAUDULENT FINANCIAL REPORTING DENGAN KOMITE AUDIT SEBAGAI VARIABEL MODERASI (Studi Empiris Pada Perusahaan Manufaktur yang terdaftar di BEI tahun 2016 – 2018). PROSIDING SEMINAR NASIONAL CENDEKIAWAN, 2. https://doi.org/10.25105/semnas.v0i0.5774
-
Saragih, A. D., & Dewayanto, T. (2023). Systematic Literature Review : Dampak Teknologi Big Data Analytics Dalam Mendeteksi Fraud Pada Bidang Audit. Diponegoro Journal of Accounting, 12(3), 1–9. http://ejournal-s1.undip.ac.id/index.php/accounting
-
Syahputra, B. E., & Afnan, A. (2020). Pendeteksian Fraud: Peran Big Data dan Audit Forensik. Jurnal ASET (Akuntansi Riset), 12(2), 301–316. https://doi.org/10.17509/jaset.v12i2.28939
-
Tandiontong, M. (2016). Kualitas Audit dan Pengukurannya. Alfabeta.
-
Tang, J., & Karim, K. E. (2017). Big Data in Business Analytics: Implications for the Audit Profession. The CPA Journal, 87(6), 34–39. https://www.cpajournal.com/2017/06/26/big-data-business-analytics-implications-audit-profession/
-
Tunggal, A. W. (2016). Aspek - Aspek Audit Kecurangan. Harvarindo.
-
Wawo, A. (2022). Pengaruh Kualitas Audit dan Whistleblowing System Terhadap Pendeteksian Fraud. SEIKO : Journal of Management & Business, 5(2), 681–696. https://doi.org/10.37531/sejaman.vxix.2353
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