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Contact Name
Eko Siswanto
Contact Email
kompak@stekom.ac.id
Phone
+6285640236283
Journal Mail Official
kompak@stekom.ac.id
Editorial Address
Jl. Majapahit No.605, Pedurungan Kidul, Kec. Pedurungan, Kota Semarang, Jawa Tengah 50192
Location
Kota semarang,
Jawa tengah
INDONESIA
Kompak : Jurnal Ilmiah Komputerisasi Akuntansi
ISSN : 1979116X     EISSN : 26216248     DOI : https://doi.org/10.51903/kompak.v14i1
Core Subject : Education,
Kompak :Jurnal Ilmiah Komputerisasi Akuntansi merupakan Jurnal yang diterbitkan oleh UNIVERSITAS SAINS DAN TEKNOLOGI KOMPUTER (STEKOM). Jurnal ini terbit 2 kali dalam setahun yaitu pada bulan Juli dan Desember. Misi dari Jurnal Kompak adalah untuk menyebarluaskan, mengembangkan dan menfasilitasi hasil penelitian mengenai Ilmu bidang Ekonomi dan Manajemen, sebagai media bagi para dosen, guru, peneliti dan para praktisi dalam bidang Ekonomi dan Manajemen dari seluruh Indonesia, dalam melakukan pertukaran informasi tentang hasil-hasil penelitian terbaru yang telah dilakukan.
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Articles 11 Documents
Search results for , issue "Vol. 18 No. 2 (2025): Kompak : Jurnal Ilmiah Komputerisasi Akuntansi" : 11 Documents clear
Social Media Digital Footprints for Strengthening Corporate Forensic Auditing Practices Listyaningrum, Heni Dwi
Kompak :Jurnal Ilmiah Komputerisasi Akuntansi Vol. 18 No. 2 (2025): Kompak : Jurnal Ilmiah Komputerisasi Akuntansi
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/kompak.v18i2.3130

Abstract

The rapid growth of social media has yielded vast digital traces with high potential for improving corporate forensic auditing. Their utilization, however, lags behind through technological reliability, privacy, and adherence to the law. The aim of this study is to explore effective utilization of social media digital traces in forensic auditing and develop a functional framework that lags neither behind through technological efficiency nor adherence to the law and ethics. A mixed-method design was utilized, combining quantitative machine learning analysis with qualitative document analysis and semi-structured interview insight. Quantitative data drawn from social media digital traces were processed using Random Forest algorithm with SMOTE for class balancing, while qualitative data were processed using thematic analysis. The results indicated high model performance with 91.3% accuracy and AUC-ROC of 0.94, together with three emergent themes: digital integration, ethics and privacy, and regulation and legality. The results demonstrate that digital footprints may serve as an effective early and reliable indicator for fraud detection, provided they are accompanied by clear regulatory and ethical frameworks. Its principal contribution lies in the development of an operational model that combines machine learning with legal and ethical perspectives, a new strategy which matures methodological refinement and practical application in today's forensic auditing.

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