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All Journal Accounting Student Series on Emerging Trends
Si Made Ngurah
Universitas Halu Oleo
Economics, Econometrics & Finance

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INTEGRASI SISTEM INFORMASI AKUNTANSI DENGAN TEKNOLOGI BIG DATA DAN ARTIFICIAL INTELLIGENCE: TINJAUAN LITERATUR SISTEMATIS Si Made Ngurah
Accounting Student Series on Emerging Trends Vol. 1 No. 01 (2026): Navigasi Pengelolaan Keuangan di Era Transformasi Digital dan Kepatuhan Korpor
Publisher : Jurusan Akuntansi, Universitas Halu Oleo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66896/asset.1.01.2026.29

Abstract

This study aims to map the trends, benefits, challenges, and integration models of Big Data and artificial intelligence (AI) in accounting information systems (AIS) during the period 2020 to 2025. The method employed is a systematic literature review (SLR) adopting the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. The literature search was conducted on the Scopus database using Boolean keywords combining terms related to AIS, Big Data, and AI. From 582 articles identified, the selection process yielded 50 articles meeting all inclusion criteria for further analysis. The findings reveal that publication trends have grown consistently, with machine learning as the most dominantly applied AI technology (60%), followed by natural language processing (36%) and robotic process automation (28%). Key benefits of integration include improved operational efficiency, data accuracy, fraud detection, and faster decision-making. The most significant challenges involve data security and privacy, availability of skilled human resources, high implementation costs, and immature regulatory frameworks. This study also identifies the need for longitudinal research, exploration of AI ethics, and development of adoption frameworks for small and medium-sized accounting organizations.
EVALUASI MODEL ALTMAN Z-SCORE PADA KONDISI NEGATIVE EQUITY: STUDI KASUS PT WIJAYA KARYA TAHUN 2025 Si Made Ngurah
Accounting Student Series on Emerging Trends Vol. 1 No. 02 (2026): Sinergi Akuntansi, Tata Kelola, dan Pembangunan Ekonomi — Kajian Multisektoral
Publisher : Jurusan Akuntansi, Universitas Halu Oleo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66896/asset.1.02.2026.32

Abstract

This study analyzes the ability of the Altman Z-Score model in predicting financial distress at PT Wijaya Karya (Persero) Tbk from 2022 to 2025. The method employed is descriptive quantitative using documentation of audited annual consolidated financial statements. Data components include working capital, retained earnings, EBIT, market value equity, and net sales relative to total assets. The results indicate that WIKA's Z-Score consistently remained in the distress zone (Z < 1.81) for four consecutive years. In 2022, the Z-Score was recorded at 0.35, improved slightly to 0.43 in 2023, then declined to 0.30 in 2024 and collapsed to negative 0.06 in 2025. The three primary drivers of degradation were retained earnings shifting to negative reflecting negative equity conditions, consecutive negative EBIT signaling operational failure, and working capital erosion indicating liquidity pressure. The most significant finding is the three-year temporal gap between the early Z-Score warning signal (2022) and the filing of four PKPU claims (March 2025) along with trading suspension by the Indonesia Stock Exchange (late 2025). This gap demonstrates that Z-Score provides adequate early warning but was not optimally responded to by stakeholders. The model exhibits limitations in handling negative equity and implicit government guarantees typical of state-owned construction enterprises, yet the directional prediction signal remains valid.
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