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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
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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

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Journal : diponegoro journal of accounting

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ANALISIS PENGARUH GOOD CORPORATE GOVERNANCE INDEX DAN KEPEMILIKAN INSTITUSIONAL TERHADAP KINERJA PERUSAHAAN Putra, Idam Manik Setia; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 8, Nomor 4, Tahun 2019
Publisher : Diponegoro Journal of Accounting

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Abstract

This study aims to exmine the effect of good corporate governance index, sub-index, and institutional ownership as independent variable toward firm performance as dependent variable. This research develops a governance index consisting of 33 indicators to measure the corporate governance index. This study uses secondary data obtained from the Indonesia stock exchange (idx). This research using a sample as many as 269 manufacturing companies registered in BEI year 2015 – 2017. The methods used in this research is purposive sampling method. Statistical techniques used in this study is a multiple regression. The results obtained from this research shows the good corporate governance index, sub-index has the significant positive influence on the firm performance, and institutional ownership has the significant negative influence on the firm performance. However, not all elements of corporate governance appear to have a significant effect on firm performance.
PENGARUH KUALITAS AUDIT DAN KUALITAS PELAPORAN KEUANGAN TERHADAP EFISIENSI INVESTASI PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEI PADA TAHUN 2017 – 2019 Firawan, Panji Aldy; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 10, Nomor 4, Tahun 2021
Publisher : Diponegoro Journal of Accounting

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This study aims to examine the effect of audit quality and financial reporting quality on investment efficiency where the variables used in this study are the dependent variable (investment efficiency) and the independent variable (audit quality and financial reporting quality). The population in this study are sector manufacture listed on the Indonesia Stock Exchange for the 2017-2019 period. The sample was taken by using purposive sampling method. Based on the purposive sampling method, the samples obtained were 113 sampel data for three consecutive years (2017-2019). The analytical method used in this research is multiple linear regression analysis.The results in this study indicate that audit quality and financial report quality have a positive effect on efficiency investment.
PENGARUH MODAL INTELEKTUAL TERHADAP EFISIENSI OPERASIONAL PERUSAHAAN MANUFAKTUR (Studi Empiris pada Perusahaan manufaktur yang Terdaftar di Bursa Efek Indonesia Tahun 2016-2019) Rahadiansyah, Arief; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 10, Nomor 4, Tahun 2021
Publisher : Diponegoro Journal of Accounting

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Abstract

Global business competition is currently very tight, so companies are required to provide new innovations in order to remain competitive in the market. This forces the company to have highly intellectual human resources. Because to remain competitive in the market the company must be able to provide products that have the same quality as in the market but at a lower price than the market, so the company must be able to produce low operating costs in order to reduce the selling price in the market. This study aims to test the M-VAIC, HCE, RCE, and CEE hypotheses on the company's operational efficiency. The method used in this study is purposive sampling with a total sample of 101 research samples in the manufacturing sector listed on the Indonesia Stock Exchange in 2016-2019. The analysis technique used is multiple regression and using a cross-section data model. The results of this study indicate that RCE and CEE have a significant positive relationship to the company's operational efficiency.
PENERAPAN ARTIFICIAL INTELLIGENCE, BIG DATA, DAN BLOCKCHAIN DALAM FINTECH PAYMENT TERHADAP RISIKO PENIPUAN KOMPUTER (COMPUTER FRAUD RISK): A SYSTEMATIC LITERATURE REVIEW Caseba, Farah Labibah; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

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This research is aimed at finding out the benefits, driving factors and challenges of applying artificial intelligence, big data and blockchain to fintech payments in preventing the risk of computer fraud. This research uses the systematic literature review (SLR) method by analyzing articles obtained through literature selection related to the research objectives. Articles were obtained based on keywords, published in Scopus indexed academic journals published from 2020 to 2024, and other inclusion criteria in the research. This research uses twenty selected articles according to research criteria which will be analyzed further. The systematic literature review (SLR) method is used with the aim of collecting and evaluating related research systematically and avoiding subjective identification. This research found that the application of artificial intelligence, big data and blockchain in fintech payments can prevent the risk of computer fraud. The optimal combination of artificial intelligence, big data and blockchain technology provides many benefits and conveniences in fintech payments. However, it is necessary to consider the challenges and risks that arise as technology continues to develop. It is hoped that these findings will provide benefits for future researchers, companies in related fields, and fintech payment users in everyday life.
INTEGRASI BLOCKCHAIN DAN ARTIFICIAL INTELLIGENCE PADA KURIKULUM AKUNTANSI: SYSTEMATIC LITERATURE REVIEW Adrian, Fariz Hudi; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

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This study aims to conduct research on the integration of blockchain and artificial intelligence in the accounting curriculum in accounting education institutions. This research uses the systematic literature review (SLR) method in analyzing 20 articles published on the Scopus database with a range of years published 2021-2024. The literature search design guidelines use the PICO framework and articles are screened using the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) protocol. The results of the analysis in this study state that the current accounting curriculum needs to be updated to meet the needs of a rapidly growing industry with modern technology. The integration of fintech, blockchain, and artificial intelligence is essential to ensure graduates have skills that are relevant to the demands of the job market and reduce the gap between employer expectations and graduate skills. The integration of these technologies in the accounting curriculum will increase the relevance and modernization of learning materials, improve the quality of education, and encourage innovation in teaching. However, there are challenges to be faced, such as a crowded curriculum, lack of resources and expertise of educators, and privacy and security concerns. However, with global market pressures, adaptive organizational cultures, technological benefits, collaborative support, and adequate infrastructure, this integration can be managed wisely to prepare students for digital transformation and open up wider career opportunities.
PERAN BIG DATA ANALYTICS, MACHINE LEARNING, DAN ARTIFICIAL INTELLIGENCE DALAM PENDETEKSIAN FINANCIAL FRAUD: A SYSTEMATIC LITERATURE REVIEW Dewi, Finecia Shinta; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

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This research aims to explore the critical role of big data analytics, machine learning, and artificial intelligence in detecting financial fraud within financial institutions. The research based on published research articles. Utilizing a Systematic Literature Review with the PRISMA protocol, an analysis was conducted on 20 articles published between 2020 and 2024, sourced from the Scopus database. The findings were categorized into three areas: the role of big data analytics in financial fraud detection, the role of machine learning in financial fraud detection, and the role of artificial intelligence in financial fraud detection. The results indicated that financial fraud detection systems employing big data analytics (BDA) demonstrated a significant average strength (76.67%), particularly in detection effectiveness, accuracy, and data processing speed. The implementation of artificial intelligence (AI) in detection also showed significant strength scores. In contrast to BDA and AI, some machine learning algorithms exhibited substantial weaknesses. Addressing these weaknesses in financial fraud detection at financial institutions, future research on the integration of machine learning algorithms is deemed crucial.
PENERAPAN TEKNOLOGI ARTIFICIAL INTELLIGENCE DAN BLOCKCHAIN DALAM MENDETEKSI FRAUD PADA PROSES AUDIT: SYSTEMATIC LITERATURE REVIEW Syahronny, Muhammad Ray; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

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Abstract

This study aims to understand the importance of applying artificial intelligence and blockchain technology to detect fraud in the audit process based on published research articles. It also captures empirical research related to artificial intelligence and blockchain and seeks to identify their differences, thereby serving as a guide for future empirical research. The study uses the systematic literature review (SLR) method to analyze various articles published in the Scopus database within the publication range of 2020-2024. The articles were filtered using the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) reporting guidelines. A total of twenty articles were synthesized to answer the research questions. The analysis results of this study indicate that the application of artificial intelligence and blockchain technology had a positive impact on detecting fraud in the audit process. Artificial intelligence improves the accuracy of automatic fraud detection, while blockchain provides transparent and valid data. However, there are still potential risks and challenges in applying artificial intelligence and blockchain technology to detect fraud in the audit process. Factors such as information security, information technology, and human resources influence auditors in adopting artificial intelligence and blockchain technology. This study is expected to provide substantial benefits to auditors by raising awareness for further professional skill development and recognizing the impact of technology.
PENERAPAN MACHINE LEARNING DAN DEEP LEARNING PADA PENINGKATAN DETEKSI CREDIT CARD FRAUD - A SYSTEMATIC LITERATURE REVIEW Tarissa, Berliana Via; Dewayanto, Totok
Diponegoro Journal of Accounting Volume 13, Nomor 3, Tahun 2024
Publisher : Diponegoro Journal of Accounting

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This research aims to explore the application of machine learning and deep learning in enhancing credit card fraud detection and identifying gaps in knowledge that could serve as a foundation for future research.The study utilized the systematic literature review (SLR) method to analyze various articles published in Scopus-indexed journals between 2020 and 2024. Article selection followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, resulting in the inclusion of twenty top-tier articles based on predefined keywords. The findings indicate that machine learning and deep learning significantly improve the accuracy and efficiency of fraud detection by effectively identifying complex fraud patterns that are challenging to detect using traditional methods, thereby reducing false alarms. Several algorithms such as Random Forest, XGBoost, Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) demonstrated high performance in classifying transactions as legitimate or fraudulent. The integration of these algorithms also has the potential to enhance overall system performance. The implementation of machine learning and deep learning not only strengthens the security of current fraud detection systems but also prepares financial institutions to tackle future challenges. Further adaptation to increasingly complex fraud patterns is crucial for enhancing financial transaction security in the digital era. Therefore, the development of more innovative and adaptive algorithm combinations is necessary to meet the growing security demands in the modern financial world.
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

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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

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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.
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 Indah, Indah Dwi Novianti Irmadhani, Aldina Syifa Nur Malik, Muhammad Fahad Marsono Nadia Husnaningtyas 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