Article Per Year (5 Year)
p-Index From 2021 - 2026
3.554
P-Index
This Author published in this journals
All Journal Diponegoro Journal of Accounting Jurnal Dinamika Akuntansi JEMA: Jurnal Ilmiah Bidang Akuntansi dan Manajemen Fokus Ekonomi Jurnal ULTIMA Accounting Jurnal STIE Semarang (Edisi Elektronik) Asia Pacific Fraud Journal Jurnal Ilmu Manajemen dan Akuntansi Terapan International Journal of Economics, Business and Accounting Research (IJEBAR) JOURNAL SCIENTIFIC OF MANDALIKA (JSM) International Journal of Business, Technology, and Organizational Behavior (IJBTOB) JRABA
Totok Dewayanto
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

Published : 28 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 28 Documents
Search

 1   2   3 
PENGARUH SOSIALISASI PERPAJAKAN, KESADARAN WAJIB PAJAK, PEMAHAMAN PERPAJAKAN, DAN TARIF PAJAK TERHADAP KEPATUHAN WAJIB PAJAK PELAKU E- COMMERCE (Studi kasus pada Pelaku Usaha UMKM yang Menggunakan Layanan Berbasis E-commerce di Kabupaten Jepara) Hidayat, Kira Ninda Sarasati; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 2, Tahun 2024
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to determine the effect of tax socialization, taxpayer awareness, understanding of taxation, and tax rates on the compliance of e- commerce taxpayers.This study used primary data that distributed all questionnaires online through a google form obtained by a sample of 31 respondents using the voluntary sampling method. The population in this study is MSME taxpayers, business actors who use e-commerce services. The data obtained were analyzed using multiple regression analysis using the SPSS 23 analysis program.The results of this study show that tax socialization has a positive and significant effect on taxpayer compliance. Meanwhile, taxpayer awareness, understanding of taxation, and tax rates have a positive and insignificant effect on taxpayer compliance.
PENERAPAN MACHINE LEARNING, DEEP LEARNING, DAN DATA MINING DALAM DETEKSI KECURANGAN LAPORAN KEUANGAN - A SYSTEMATIC LITERATURE REVIEW Prasetyo, Sindu; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to determine the impact of the application of machine learning, deep learning, and data mining in financial statement fraud detection based on published research articles. This research also aims to explore the gaps in knowledge to develop future academic studies.The method used in this research is Systematic Literature Review (SLR) to analyze various articles published in academic journals indexed in Scopus from 2020 to 2024. The articles were filtered using predetermined keywords obtained from various top-ranked journals, resulting in twenty-one articles being reviewed. This SLR method was used to examine the topics, results, methodology, recommendations and limitations of the published articles. The analysis provides evidence that machine learning, deep learning, and data mining have a positive impact on financial statement fraud detection. The adoption of these technologies can assist auditors in improving the accuracy of fraud detection. New technologies such as machine learning, deep learning, and data mining can find hidden patterns contained in data and are able to find relationships between each component of the data. In addition, this research also identifies the weaknesses and strengths of the algorithms used in fraud detection. This study also provides recommendations for future research, including the development of more sophisticated algorithms, identifying factors inhibiting the adoption of these technologies in financial statement fraud detection.
PENGARUH CORPORATE GOVERNANCE DAN STRUKTUR KEPEMILIKAN TERHADAP KINERJA KEUANGAN (Studi Empiris pada Perusahaan Pertambangan yang Terdaftar di Bursa Efek Indonesia pada Tahun 2020-2022) Firdaus, Faiq Fadhil; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to examine the influence of ownership structure and Corporate Governance on financial performance. The dependent variable in this study is financial performance as measured by Tobins'q and the independent variable in this study is Corporate Governance which is measured by board size which is the number of board of commissioners and directors, and board independence which affects financial performance activities while Ownership structure is measured using managerial and foreign ownership.  The population in this study is mining companies listed on the Indonesia Stock Exchange (IDX) in 2020-2022. Sampling to collect data using the purposive sampling method. The sample used in this research was 180 companies with 60 companies per year for 3 years. The analysis test in this research uses multiple regression analysis. The research results show that board size has a positive effect on financial performance. Then, board independence has no effect on financial performance. Institutional ownership has a significant positive impact on financial performance.
PENGGUNAAN BERBAGAI ARTIFICIAL INTELLIGENCE PADA PROSES AUDIT- A SYSTEMATIC LITERATURE REVIEW Silaen, Raymonth Pieter; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 2, Tahun 2024
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to determine the importance of using various artificial intelligence in the audit process. The method used in this research is Systematic Literature Review (SLR) by searching for articles in the Scopus database. The research results show that the application of AI in the audit process can increase audit efficiency and effectiveness. Apart from that, AI also helps auditors with data analysis and fraud detection. However, there are several obstacles to using AI in audits, such as the auditor's lack of understanding of AI technology. This research is expected to contribute to the development of science and technology, especially in the audit field. In addition, the results of this research are expected to provide benefits for auditors in carrying out the audit process. In this research, the author found 20 articles that were relevant to the research topic. This research concludes by discussing the implications of the research for the future of auditing. The findings show that AI has the potential to significantly improve the efficiency, accuracy, and effectiveness of the audit process. However, there are challenges that need to be overcome, such as the need for auditors to develop new skills and regulatory adaptation to the use of AI in audits.
PERAN MACHINE LEARNING DAN DEEP LEARNING DALAM PENDETEKSIAN PENCUCIAN UANG – A SYSTEMATIC LITERATURE REVIEW Hanin, Ghalizha Failazufah; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to explore and uncover the complex phenomena in the financial world, particularly concerning the prevention and mitigation of money laundering, which is becoming increasingly rampant. In an era of advancing technology, the application of artificial intelligence such as machine learning and deep learning has become essential to enhance the effectiveness of anti-money laundering systems. This research employs a systematic literature review to analyze the role of AI, machine learning, and deep learning in detecting money laundering techniques. By collecting and systematically selecting 20 articles from the Scopus database, this study provides insights into the driving factors influencing the adoption and implementation of these technologies to combat money laundering. The findings highlight the importance of advanced technology in improving compliance, security, and the speed of detection, ultimately contributing to the development of more effective anti-money laundering strategies.
PERAN CORPORATE GOVERNANCE TERHADAP KUALITAS PELAPORAN KEUANGAN – A SYSTEMATIC LITERATURE REVIEW Raharjo, Hana Jovita; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Corporate governance has a role in the quality of financial reporting therefore companies need to use corporate governance to enhance managerial oversight and stop opportunistic conduct. This study aims to determine the role of internal audit, CEO, board of directors, supervisory board, share ownership, audit committee, and public accounting firm on financial reporting quality and research directions that can be explored in the future. The systematic review methodology used in this study is a qualitative method. This research used secondary data derived from the results of research published in journals in the form of online articles. This systematic literature review covers twenty English- language articles published in 2019-2023 and included in Scopus indexed journals. The results showed that some corporate governance mechanisms consistently show that their characteristics play an important role in the quality of financial reporting, the impact of various characteristics of various other corporate governance mechanisms is different.
PENINGKATAN KINERJA PERUSAHAAN MELALUI IMPLEMENTASI SISTEM ENTERPRISE RESOURCE PLANNING DAN SUPPLY CHAIN MANAGEMENT - A SYSTEMATIC LITERATURE REVIEW Fahrezi, Moh. Nanda Putra; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 1, Tahun 2024
Publisher : Diponegoro Journal of Accounting

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study discusses the implementation of Enterprise Resource Planning (ERP) and Supply Chain Management (SCM) systems and their impact on improving company performance. A systematic literature review of articles indexed in SCOPUS was utilized to analyze and synthesize findings related to the topic. The research demonstrates that the implementation of ERP and SCM systems holds significant potential for enhancing company performance. However, the primary challenge lies in addressing critical factors that influence the success of the implementation, such as user satisfaction, complexity, training, user engagement, management support, and compatibility. User satisfaction is considered the most crucial factor in ERP and SCM implementation. If users feel content with the system's usability, they will be more motivated to maximize its benefits in their daily work. Additionally, complexity needs to be carefully addressed and can be overcome through adequate training, active user engagement, and strong top management support. The implementation of ERP and SCM systems positively impacts company performance through increased operational efficiency, cost reduction, faster response times, and improved customer satisfaction. However, the sustainability of system usage also requires attention, particularly concerning factors such as user engagement, continuous training, and periodic evaluations. This research provides a comprehensive understanding of the relationship between ERP and SCM implementation and the enhancement of company performance. The practical implication of this study is that organizations must pay attention to critical factors influencing implementation and ensure that system usage is effectively managed within their business context. Although this research contributes significantly to the understanding of ERP and SCM implementation, there are limitations related to the number of literature sources used, resulting in less variation in the findings. Therefore, further research is needed, involving a broader analysis of literature, to enrich the understanding of ERP and SCM system implementation and its impact on improving company performance.
FINANCIAL FRAUD DETECTION AND MACHINE LEARNING ALGORITHM (UNSUPERVISED LEARNING): SYSTEMATIC LITERATURE REVIEW Husnaningtyas, Nadia; Totok Dewayanto
Jurnal Riset Akuntansi Dan Bisnis Airlangga Vol 8 No 2 (2023): Jurnal Riset Akuntansi dan Bisnis Airlangga
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jraba.v8i2.49927

Abstract

This research aims to assess the usage of unsupervised learning in detecting financial fraud across various financial industries by identifying cognitive constructs, benefits, economic optimization, and challenges associated with fraud detection necessitating innovative approaches for effective detection. This study conducts Systematic Literature Review following PRISMA protocol for article selection of 27 journal articles published between 2010 and 2023, sourced from Scopus database. The analysis discloses that unsupervised learning has been implemented across diverse financial sectors, including online payments, insurance, and prominently in banking, especially for identifying anomalies in credit card transactions. K-Means is the most popular method used in unsupervised learning. Nevertheless, there are ongoing challenges that require solutions to ensure the efficacy of machine learning implementation, encompassing issues like class imbalance and the complexity of fraudulent activities. In theoretical terms, this research provides an understanding of cognitive concepts, benefits and applications, challenges, and practical recommendations in the use of unsupervised learning for financial fraud detection. This is useful for practical implementation, benefiting industry practitioners in selecting appropriate models with datasets that have the potential to enhance detection system accuracy and reduce financial losses due to fraud.
FRAUD DIAMOND DAN KECURANGAN PELAPORAN KEUANGAN PADA SAAT SEBELUM DAN SAAT COVID-19 DENGAN GOOD CORPORATE GOVERNANCE SEBAGAI VARIABEL MODERATING Hastuti, Indhi; Dewayanto, Totok
Jurnal Ilmu Manajemen dan Akuntansi Terapan (JIMAT) Vol. 13 No. 2 (2022): Jurnal Ilmu Manajemen dan Akuntansi Terapan (JIMAT)
Publisher : Sekolah Tinggi Ilmu Ekonomi Totalwin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (319.276 KB) | DOI: 10.36694/jimat.v13i2.428

Abstract

The phenomenon that is currently happening is covid-19, in this research the researcher wanted to know before and during covid-19 whether there was fraud in financial reporting by using fraud diamonds to detect the fraud. The sample used is a manufacturing company with a period of 2018 - 2020.This study uses the independent variable external pressure for DAR proxy, financial target for ROA proxy, nature of industry for Inventory proxy, change in auditor and change in director. Good corporate governance is also used in this study as a moderating variable. The data processing used by the researcher is SPSS version 20.0. The results of this study indicate that the independent variable external pressure has an influence on fraudulent financial reporting either before or during covid-19 and also when using moderating variables.
A systematic review of anti-money laundering systems literature: Exploring the efficacy of machine learning and deep learning integration Husnaningtyas, Nadia; Hanin, Ghalizha Failazufah; Dewayanto, Totok; Malik, Muhammad Fahad
JEMA: Jurnal Ilmiah Bidang Akuntansi dan Manajemen Vol. 20 No. 1 (2023): JEMA: Jurnal Ilmiah Bidang Akuntansi dan Manajemen
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31106/jema.v20i1.20602

Abstract

Money laundering is a complex issue with global impact, leading to the increased adoption of artificial intelligence (AI) to bolster anti-money laundering (AML) measures. AI, with machine learning and deep learning as key drivers, has become an essential enhancement for AML strategies. Recognizing this emerging trend, this study embarks on a systematic literature review, aiming to provide novel insights into the implementation, effectiveness, and challenges of these sophisticated computational techniques within AML frameworks. A critical analysis of 26 selected studies published from 2018 to 2023 highlights the essential role of machine learning and deep learning in identifying money laundering schemes. Notably, the decision tree algorithm stands out as the most commonly utilized technique. The combined use of both learning models has proven to significantly increase the effectiveness of AML systems in detecting suspicious financial patterns. However, the optimization of these advanced methods is still constrained by issues related to data complexity, quality, and access.
Co-Authors Adrian, Fariz Hudi Caseba, Farah Labibah Dewi, Finecia Shinta Dwi Ratmono Fahrezi, Moh. Nanda Putra Firawan, Panji Aldy Firdaus, Faiq Fadhil Hanin, Ghalizha Failazufah Hastuti, Indhi Herlina Herlina Hidayat, Kira Ninda Sarasati Husnaningtyas, Nadia Indah, Indah Dwi Novianti Irmadhani, Aldina Syifa Nur Malik, Muhammad Fahad Marsono Nugraha, Agung Setya Nur Cahyonowati Prasetyo, Sindu Putra, Idam Manik Setia Rahadiansyah, Arief Raharjo, Hana Jovita Sari Indra Pratama Silaen, Raymonth Pieter Syahronny, Muhammad Ray Tarissa, Berliana Via