Pengaruh Big Data Analytics, Artificial Intelligence, dan Kompetensi Auditor terhadap Kualitas Audit pada Kantor Akuntan Publik Jakarta

Abstrak

ABSTRAK
Penelitian ini difokuskan pada analisis pengaruh Big Data Analytics, Artificial Intelligence, dan Kompetensi Auditor terhadap Kualitas Audit pada Kantor Akuntan Publik di Jakarta Selatan. Penelitian ini menggunakan metode kuantitatif kausalitas dengan data primer melalui penyebaran kuesioner. Sampel penelitian dipilih dengan teknik purposive sampling, dan data dianalisis menggunakan metode PLS-SEM melalui SmartPLS 3.0. Hasil penelitian menunjukkan bahwa Big Data Analytics tidak berpengaruh terhadap kualitas audit dengan nilai t-statistik 0,264, p-value 0,792, dan original sample 0,021, yang menandakan pemanfaatan Big Data Analytics masih rendah dan kalah dengan metode tradisional. Artificial Intelligence berpengaruh positif dan signifikan terhadap kualitas audit dengan nilai t-statistik 2,943, p-value 0,003, dan original sample 0,270, Hal ini menunjukkan bahwa peningkatan Artificial Intelligence akan meningkatkan kualitas audit karena dinilai mudah digunakan, bermanfaat nyata, dan mendukung kinerja auditor secara keseluruhan. Kompetensi auditor juga berpengaruh positif dan signifikan terhadap kualitas audit dengan nilai t-statistik 11,461, p-value 0,000, dan original sample 0,707, Hal ini menunjukkan bahwa peningkatan kompetensi auditor akan meningkatkan kualitas audit karena auditor yang kompeten mampu mengandalkan kemampuan internal dan memanfaatkan teknologi secara efektif sehingga menghasilkan audit yang andal dan bernilai.

ABSTRACT
This study aims to examine the influence of Big Data Analytics, Artificial Intelligence, and Auditor Competence on Audit Quality at Public Accounting Firms in South Jakarta. This research employs a causal quantitative method using primary data collected through questionnaires. The sample was selected using purposive sampling, and the data were analyzed using the PLS-SEM method through SmartPLS 3.0. The results show that Big Data Analytics has no effect on audit quality, with a t-statistic value of 0.264, p-value of 0.792, and an original sample of 0.021, indicating that the utilization of Big Data Analytics remains low and is outperformed by traditional methods. Artificial Intelligence has a positive and significant effect on audit quality, with a t-statistic value of 2.943, p-value of 0.003, and an original sample of 0.270. This indicates that an increase in Artificial Intelligence will improve audit quality, as it is considered easy to use, provides tangible benefits, and supports auditor performance as a whole. Auditor competence also has a positive and significant effect on audit quality, with a t-statistic value of 11.461, p-value of 0.000, and an original sample of 0.707. This indicates that an increase in auditor competence will enhance audit quality, as competent auditors are able to rely on their internal capabilities and effectively leverage technology to produce reliable and valuable audit results.