Pengaruh keahlian auditor terhadap deteksi kecurangan dengan aplikasi computer assisted audit techniques (caat) sebagai variabel pemoderasi
Info Katalog
File Repositori
Subyek : Accounting--Computer-assisted instruction;Fraud - Detection
Penerbit : FEB - Usakti
Kota Terbit : Jakarta
Tahun Terbit : 2025
Pembimbing 1 : Harti Budi Yanti
Kata Kunci : technical and analytical skills, accounting dan auditing skills, psycho-social skills, effective com
Status Posting : Published
Status : Lengkap
File Repositori
| No. | Nama File | Hal. | Link |
|---|---|---|---|
| 1. | 2024_TS_MAK_123012011029_Halaman-Judul.pdf | 13 | |
| 2. | 2024_TS_MAK_123012011029_Surat-Pernyataan-Revisi-Terakhir.pdf | 1 | |
| 3. | 2024_TS_MAK_123012011029_Surat-Hasil-Similaritas.pdf | 1 | |
| 4. | 2025_TS_MAK_123012011029_Halaman-Pernyataan-Persetujuan-Publikasi-Tugas-Akhir-untuk-Kepentingan-Akademis.pdf | 1 | |
| 5. | 2024_TS_MAK_123012011029_Lembar-Pengesahan.pdf | 5 | |
| 6. | 2024_TS_MAK_123012011029_Pernyataan-Orisinalitas.pdf | 1 | |
| 7. | 2025_TS_MAK_123012011029_Formulir-Persetujuan-Publikasi-Karya-Ilmiah.pdf | 1 | |
| 8. | 2024_TS_MAK_123012011029_Bab-1.pdf | 10 | |
| 9. | 2024_TS_MAK_123012011029_Bab-2.pdf | 23 |
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| 10. | 2024_TS_MAK_123012011029_Bab-3.pdf | 11 |
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| 11. | 2024_TS_MAK_123012011029_Bab-4.pdf | 28 |
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| 12. | 2024_TS_MAK_123012011029_Bab-5.pdf | 3 | |
| 13. | 2024_TS_MAK_123012011029_Daftar-Pustaka.pdf | 8 | |
| 14. | 2024_TS_MAK_123012011029_Lampiran.pdf | 12 |
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P Penelitian ini bertujuan untuk menganalisis pengaruh keahlian auditor, yang mencakup technical and analytical skills, accounting dan auditing skills, psycho-social skills, effective communication skills, dan big data analytics skills terhadap deteksi kecurangan dengan aplikasi Computer Assisted Audit Techniques (CAAT) sebagai variabel pemoderasi. Data penelitian ini diperoleh dari pengumpulan kuesioner atas 142 responden yang merupakan pemeriksa pada Badan Pemeriksa Keuangan Republik Indonesia (BPK RI). Pengambilan sampel dilaksanakan dengan mempergunakan metode acak (simple random sampling). Selanjutnya, pengujian dalam penelitian ini dilaksanakan dengan mempergunakan model analisis statistik Structural Equation Model Partial Least Square (SEM-PLS) mempergunakan perangkat lunak SmartPLS. Hasil penelitian memperlihatkan effective communication skills, big data analytics skills, dan aplikasi CAAT berpengaruh terhadap deteksi kecurangan. Selain itu, aplikasi CAAT tidak memperkuat pengaruh big data analytics skills terhadap deteksi kecurangan. Berdasarkan nilai koefisien determinasi, technical and analytical skills, accounting dan auditing skills, psycho-social skills, effective communication skills, big data analytics skills, dan aplikasi CAAT secara bersama-sama memberikan pengaruh terhadap deteksi kecurangan sebesar 58,00% dan Sisanya sebesar 42,00% dipengaruhi oleh faktor lain di luar model.
T This study aims to analyze the influence of auditor expertise, consisting of technical and analytical skills, accounting and auditing skills, psycho-social skills, effective communication skills, and big data analytics skills on fraud detection with the application of Computer Assisted Audit Techniques (CAAT) as a moderating variable. The data for this study were obtained from collecting questionnaires from 142 respondents who were auditors at the Audit Board of the Republic of Indonesia (BPK RI). Sampling was carried out using a random method (simple random sampling). Furthermore, testing in this study was carried out using the Structural Equation Model Partial Least Square (SEM-PLS) statistical analysis model using SmartPLS software. The results of the study indicate that effective communication skills, big data analytics skills, and CAAT applications have an effect on fraud detection. In addition, the CAAT application does not strengthen the influence of big data analytics skills on fraud detection. Based on the determination coefficient value, technical and analytical skills, accounting and auditing skills, psycho-social skills, effective communication skills, big data analytics skills, and CAAT applications together have an influence on fraud detection of 58,00% and the remaining 42,00% is influenced by other factors outside the model.