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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
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

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ANALISIS PENERIMAAN KOMPUTER MIKRO DENGAN MENGGUNAKAN TECHNOLOGY ACCEPTANCE MODEL (TAM) PADA KANTOR AKUNTAN PUBLIK (KAP) DI JAWA TENGAH Dewayanto, Totok
JURNAL STIE SEMARANG Vol 3 No 2 (2011): VOLUME 3 NOMOR 2 EDISI JUNI 2011
Publisher : Sekolah Tinggi Ilmu Ekonomi Semarang

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Abstract

The purpose of this study was to test the level of acceptance of micro computers by auditors at accounting firms in Central Java, The current auditors in accounting firms has many uses of micro computer that can be facilitate their work. The model that used to explain acceptance of micro computer is Technology Acceptance Model (TAM) with four main construct, namely perceived usefulness, perceived ease of use, attitude toward using and user acceptance.   The result were as follows: (1) Perceived ease of use significantly influence on perceived usefulness; (2) Perceived usefulness significantly influence on attitude toward using; (3) Perceived ease of use significantly influence on attitude toward using; (4) Perceived usefulness significantly influence on user acceptance; (5) Attitude toward using did not significantly influence on user acceptance.
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.
THE EFFECT OF THE IMPLEMENTATION OF PSAK 65 ON FINANCIAL PERFORMANCE Nugraha, Agung Setya; Dewayanto, Totok
International Journal of Economics, Business and Accounting Research (IJEBAR) Vol 5, No 2 (2021): IJEBAR, VOL. 05 ISSUE 02, JUNE 2021
Publisher : LPPM ITB AAS INDONESIA (d.h STIE AAS Surakarta)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijebar.v5i2.2390

Abstract

This study aims to determine the effect of accounting standards on financial performance in the performance of companies in the manufacturing sector listed on the Indonesia Stock Exchange in 2015-2019. The data used in this study are secondary data. The method in selecting the sample is purposive sampling. The number of samples in this study was 471 companies. Hypothesis testing in this study was carried out using the t statistical test. The data analysis technique used in this study is multiple linear regression analysis and moderated regression analysis using the Statistical Product and Service Solution (SPSS) version 25 for windows data processing software program. The results of this study indicate that accounting standards have a positive and significant effect on financial performance with a correlation value of 0. Keywords: accounting standards, financial 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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Abstract

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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Abstract

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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Abstract

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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Abstract

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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Abstract

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.
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