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All Journal Diponegoro Journal of Accounting Fokus Ekonomi Ekuilibrium : Jurnal Ilmiah Bidang Ilmu Ekonomi
Totok Dewayanto
Accounting Department, Economic & Business Faculty, Diponegoro University
Economics, Econometrics & Finance

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SINERGI IOT DAN SMART CONTRACTS DALAM ARSITEKTUR ERP BERBASIS BLOCKCHAIN: TINJAUAN LITERATUR SISTEMATIS Samue Libert T; Totok Dewayanto
Diponegoro Journal of Accounting Volume 15, Nomor 2, Tahun 2026
Publisher : Diponegoro Journal of Accounting

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This research aims to analyze the synergy between the Internet of Things (IoT) and smart contracts in a blockchain-based Enterprise Resource Planning (ERP) architecture through a systematic literature review. The background of this research is based on the limitations of traditional ERP systems, which still face issues related to data security, information integrity, and the potential for fraud due to their centralized nature. The development of blockchain technology offers solutions through its characteristics of decentralization, transparency, and data immutability. Furthermore, IoT enables real-time data collection from its source, reducing manual input errors. This technological integration is expected to improve the quality of accounting information systems. This synergy also has the potential to strengthen a company's internal control. Therefore, this research is crucial for understanding the transformation of digital technology-based ERP systems. The research method used is a Systematic Literature Review (SLR), which examines various relevant scientific articles. The research process involves identifying, selecting, and analyzing literature based on specific criteria. Data is analyzed qualitatively to identify patterns and research gaps. This approach provides a comprehensive overview of technology integration in ERP. The results show that the integration of blockchain, IoT, and smart contracts can improve security, transparency, and operational efficiency. Smart contracts automate business processes, while IoT improves data accuracy. However, implementation still faces challenges such as system complexity and resource constraints.
DATA ANALYTICS UNTUK AKUNTANSI MANAJEMEN DALAM SUPPLY CHAIN MANAGEMENT – A SYSTEMATIC LITERATURE REVIEW Mutiara Aisya Kamila; Totok Dewayanto
Diponegoro Journal of Accounting Volume 15, Nomor 1, Tahun 2026
Publisher : Diponegoro Journal of Accounting

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Management accounting practices and the use of Information Technology have changed significantly over the years, especially for those working in Supply Chain Management (SCM). Data analytics is now part of the decision-making process, the controlling of costs, and measuring performance. This research systematically examines the existing literature on the effect of data analytics on management accounting within SCMs, following the PRISMA Protocol and including articles published in the Scopus databases from 2022 through 2025. The systematic review indicates the manner in which data analytics aids in planning, controlling costs, and measuring performance, but also outlines critical success factors, as well as the challenges encountered while implementing data analytics. Further, the Resource-Based View of Data Analytics is presented as an Organizational Capability, which creates a means for improving the effectiveness of Management Accounting by providing valuable firm-specific insights that cannot be easily replicated, particularly when paired with Managerial Expertise, Internal Processes and Decision-Routines across SCMs. Findings are discussed in the context of Contingency Theory, which highlights the need to ensure that technology, organizational structure and the business environment are aligned. The information provided from this systematic review can aid in the creating of digital management accounting, by giving an organization a map of how to implement data analytics against SCM decision making activities.
PERAN TEKNOLOGI BLOCKCHAIN DALAM MENINGKATKAN TRANSPARANSI LAPORAN KEUANGAN : A SYSTEMATIC LITERATUR REVIEW Aldina Syifa Nur Irmadhani; Totok Dewayanto
Diponegoro Journal of Accounting Volume 14, Nomor 3, Tahun 2025
Publisher : Diponegoro Journal of Accounting

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This research aims to examine the role of blockchain technology in improving the transparency of financial statements in the field of accounting and finance. The Systematic Literature Review (SLR) method was used to analyze 34 Scopus-indexed scientific articles published between 2017-2025. The results show that blockchain has great potential in creating secure, transparent, and irreversible transactions, as well as promoting real-time financial reporting and faster decision-making. The implementation of smart contracts and Triple-Entry Accounting (TEA) also improves record-keeping efficiency and audit automation. However, the implementation of these technologies still faces challenges such as regulatory constraints, security risks, low financial and technological literacy, and technical costs and complexities. This research emphasizes the importance of financial professional adaptation and the need for blockchain standards and regulations to ensure transparency and compliance globally.
PENGGUNAAN MODEL ARTIFICIAL INTELLIGENCE DAN MACHINE LEARNING PADA PREDIKSI KEBANGKRUTAN – A SYSTEMATIC LITERATURE REVIEW Annisa Putri Ramadhani; Totok Dewayanto
Diponegoro Journal of Accounting Volume 15, Nomor 2, Tahun 2026
Publisher : Diponegoro Journal of Accounting

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This study examines the use of Artificial Intelligence (AI) and Machine Learning (ML) in corporate bankruptcy prediction through a Systematic Literature Review (SLR). The review analyzes 30 Scopus-indexed articles published between 2021 and 2025. The findings show that bankruptcy prediction has shifted from traditional statistical models to more adaptive and accurate AI/ML approaches, with dominant models including Random Forest, Gradient Boosting, LightGBM, SVM, ANN, and DNN. The significant predictors include not only financial ratios but also non-financial factors such as corporate governance and financial reporting quality. The study also identifies key challenges, including imbalanced data, overfitting, feature selection, and limited interpretability, which can be addressed through data balancing, feature selection, and explainable AI techniques. Overall, AI and ML have strong potential to improve bankruptcy prediction effectiveness when supported by high-quality data and appropriate model selection.
PERAN SERTA TANTANGAN ARTIFICIAL INTELLIGENCE DAN MACHINE LEARNING TERHADAP EFEKTIVITAS AUDIT INTERNAL: A SYSTEMATIC LITERATURE REVIEW Talent Angeliq Monica Catherine Tampubol; Totok Dewayanto
Diponegoro Journal of Accounting Volume 14, Nomor 3, Tahun 2025
Publisher : Diponegoro Journal of Accounting

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This study aims to explore the role, benefits, and challenges of applying Artificial Intelligence (AI) and Machine Learning (ML) to improve the effectiveness of internal audits. The study employed a systematic literature review (SLR) method, analyzing twenty selected articles relevant to the research question, which were indexed in Scopus between 2021 and 2025. The results indicate that AI and ML significantly enhance the effectiveness of internal audits by improving accuracy, accelerating the audit process, and enabling real-time data analysis to detect potential risks and anomalies. Furthermore, the application of these technologies allows auditors to focus more on strategic tasks and improves corporate transparency and compliance. However, the implementation of AI and ML also faces several challenges, such as inconsistent data quality, limitations in auditors' technical competencies, and data security risks. This research contributes to a more comprehensive understanding of the integration of AI and ML in internal audits and serves as a reference for further research and professional practice in the digital age. These findings are expected to benefit future researchers, companies adopting the technology, and internal auditors.
PARADOKS KEPATUHAN PAJAK UMKM INDONESIA: MODEL INTEGRATIF DAN IMPLIKASI PERGESERAN PARADIGMA KEBIJAKAN - A SYSTEMATIC LITERATURE REVIEW Fransiskus Daniawan; Totok Dewayanto
Diponegoro Journal of Accounting Volume 15, Nomor 1, Tahun 2026
Publisher : Diponegoro Journal of Accounting

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This study diagnoses the dynamic mechanisms perpetuating tax non-compliance in Micro, Small, and Medium Enterprises (MSMEs) through an integrative conceptual model. Key variables examined include internal (capacity and literacy), external (incentives and administration), and psychosocial factors (tax morale and trust). A Systematic Literature Review (SLR) is employed to evaluate the effectiveness of traditional policies and formulate a novel relationship-centric framework.Methodologically, the SLR follows the PRISMA protocol, utilizing the PICO framework for research questions. Literature searches were conducted in the Scopus database targeting open-access English journal articles published between 2021 and 2025. From an initial 791 records, the screening and data extraction process yielded 35 high-quality articles for in-depth synthesis.The results confirm that MSME non-compliance is driven by a "Vicious Cycle of Non-Compliance", originating from low literacy and complex systems (e.g., utilization problems), which ultimately erodes taxpayer morale and trust. Personalized interventions and behavioral nudges proved significantly more effective than mere coercion. Therefore, sustainable solutions require a paradigm shift by tax authorities from an enforcement-centric to a relationship-centric model, redefining success metrics toward long-term psychological contract health.
PERAN DAN TANTANGAN ARTIFICIAL INTELLIGENCE DALAM KUALITAS PELAPORAN KEUANGAN - A SYSTEMATIC LITERATURE REVIEW Lidya Caterine Gokasi Manihuruk; Totok Dewayanto
Diponegoro Journal of Accounting Volume 14, Nomor 3, Tahun 2025
Publisher : Diponegoro Journal of Accounting

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This research aims to investigate the roles, benefits, and challenges of implementing Artificial Intelligence (AI) in enhancing the quality of financial reporting. Using the Systematic Literature Review (SLR) methodology, this research analyzes relevant articles related to the research topic obtained from Scopus-indexed academic journals published between 2021 and 2024. The literature selection was carried out based on predetermined inclusion and exclusion criteria, focusing on studies that specifically discuss the application of AI in financial reporting. The analysis results are categorized into five main AI sub-technologies: Natural Language Processing (NLP), Optical Character Recognition (OCR), Predictive Analytics & Machine Learning, Generative AI, and Anomaly Detection. The study finds that AI significantly contributes to improving accuracy, operational efficiency, predictive capabilities, and audit quality in financial reporting. However, several challenges remain, including data security risks, algorithmic bias, regulatory misalignment, infrastructure limitations, and organizational resistance. The findings are expected to provide practical insights for accountants, regulators, and decision-makers, as well as a theoretical foundation for future research on AI adoption in the accounting field.
PENGARUH PROFITABILITAS, UKURAN PERUSAHAAN, DAN BOARD SIZE TERHADAP KECEPATAN PENYESUAIAN STRUKTUR MODAL: A SYSTEMATIC LITERATURE REVIEW Hamami Fildzah Fataqun; Totok Dewayanto
Diponegoro Journal of Accounting Volume 14, Nomor 3, Tahun 2025
Publisher : Diponegoro Journal of Accounting

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Establishing an optimal capital structure is essential for firms to maximize value and enhance funding efficiency. However, numerous factors, such as firm-specific characteristics and corporate governance mechanisms, affect how quickly firms adjust their capital structure toward target leverage. Therefore, this study aims to analyze the contribution of these key variables to the adjustment process. This research employs a systematic literature review by analyzing various article published in the Scopus database between 2020 and 2024. The research stages included identification, selection, and synthesis of findings to provide a comprehensive understanding of the relationships between variables. The results indicate that profitability generally impacts capital structure adjustment speed, firm size shows mixed effects, and larger boards tend to accelerate capital structure adjustment. These findings highlight the complexity of capital structure dynamics, influenced by firm-specific characteristics and corporate governance mechanism.  This study contributes academically by synthesizing prior research findings and recommending the need for an empirical approach in capital structure decision-making.
INTEGRASI ARTIFICIAL INTELLIGENCE DAN BLOCKCHAIN DALAM MENINGKATKAN TRANSPARANSI ENVIROMENTAL, SOCIAL, AND GOVERNANCE (ESG) REPORTING: SYSTEMATIC LITERATURE REVIEW Indira Sukma Lailatu; Totok Dewayanto
Diponegoro Journal of Accounting Volume 15, Nomor 1, Tahun 2026
Publisher : Diponegoro Journal of Accounting

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This study aims to analyze the integration of Artificial intelligence (AI) and blockchain in enhancing the transparency of Environmental, Social, and Governance (ESG) reporting. Using a Systematic literature review (SLR) approach across relevant international studies, the findings reveal that the integration of AI and Blockchain can improve the reliability, accuracy, and accountability of ESG data through automated analysis and transparent, immutable data recording. AI plays a role in rapidly and intelligently collecting and processing ESG data, while blockchain ensures data security and authenticity through its distributed ledger system. However, the implementation of this integration also faces several challenges, including high adoption costs, organizational resistance, limited technical expertise, and regulatory barriers. This study contributes by providing a comprehensive understanding of the potential and limitations of integrating these two technologies, while offering direction for future research and policy development aimed at strengthening transparency and Governance in ESG reporting.
Implikasi Artificial Intelligence (AI) Pada Profesi Auditor : A Systematic Literature Review Afi Syasya Safa Maharani; Totok Dewayanto
Diponegoro Journal of Accounting Volume 15, Nomor 1, Tahun 2026
Publisher : Diponegoro Journal of Accounting

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The advancement of Artificial Intelligence (AI) has driven significant transformation in auditing practices. AI's ability to process large-scale data, detect anomalies, and perform predictive analysis offers opportunities to enhance audit efficiency, accuracy, and quality. However, AI adoption also introduces new challenges related to the professionalism and ethics of the auditing profession, such as algorithmic bias, competency limitations, and potential reductions in accountability. This study aims to analyze the implications of AI use on audit process efficiency, auditor professionalism, and audit ethics. The research method used is a Systematic Literature Review (SLR) of scientific articles published between 2020 and 2025 through the Scopus database. The results indicate that AI can improve the efficiency of audit procedures through automated data testing and real-time risk detection, while also requiring auditors to develop technological competencies and higher professional skepticism. On the other hand, risks such as algorithmic bias, lack of system transparency (black box), and unclear accountability pose ethical challenges that need to be anticipated. These findings underscore the need for regulatory frameworks, ethical guidelines, and specialized training programs to ensure that the use of AI supports audit quality without compromising fundamental professional values such as integrity, objectivity, and independence. This study is expected to serve as a reference for academics, audit practitioners, and policymakers in formulating technology adaptation strategies and future research directions.
Co-Authors Afi Syasya Safa Maharani Ailsa Azaria Laksita Aldina Syifa Nur Irmadhani Alif Nur Krishnamurti Andra Domaro Saragih Anigo Trikartiko Anis Solikatun Annisa Putri Ramadhani Aryandra Anantama Aulia Dwi Paresti Daniel Ranbon Bungaran M Daniel Satrio Partogian Deny Prasetyo Djoko Suhardjanto Dzulkifli Dzulkifli Erika Fara Rosadina Fachry Rizqi Amin Fadhil Rahandika Fathaya Aji Aryonanto Fransiskus Daniawan Gabiel Gesa Widi Purnomo Gabrielle Dika Duryat Ghazna Jullab Khorraz Hamami Fildzah Fataqun Herlian Rizki Widyatama Hipolitus Hamonangan Rumahorbo Imanuel Yoka Prasetia Indira Sukma Lailatu Ivan Krisna Priantaka Karel Michael Martin Kesia Athania Purba Kevin Fatahillah Akbar Kukuh Herwibawa Kurnia Purnama Adesya Lidya Caterine Gokasi Manihuruk Lissa Damayanti Luthfi Anugrah Pribadi Maulidina Alyssa Makarima Mikha Tri Apriliani Muhammad Akmaluddin Muhammad Ilham Utama Muhammad Razan Murran Afif Wahyudi Mutiara Aisya Kamila Paris Halomoan RAHMAWATI RAHMAWATI Raihanah Shafa Shabirah Raka Bagaskara Rezaldy Adhyasa Samue Libert T Shofiyatul Masithoh Sondang Manik Talent Angeliq Monica Catherine Tampubol Windy Sulistiawati Yuliati . . Zafara Luthfiyyah