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p-Index From 2021 - 2026
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This Author published in this journals
All Journal International Journal of Cyber and IT Service Management (IJCITSM) Journal of Computer Science and Technology Application
Muchlisina Madani
REY Incorporation
Computer Science & IT Decision Sciences, Operations Research & Management Other

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The Role Information Technology in Increasing the Effectiveness Accounting Information Systems and Employee Performance Aoliyah Firasati; Fadhila Azzahra; Sausan Raihana Putri Junaedi; Amelia Evans; Muchlisina Madani; Fitra Putri Oganda
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 4 No. 2 (2024): October
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ijcitsm.v4i2.167

Abstract

This study explores the mportant role of Information Technology (IT) in enhancing the effectiveness of Accounting Information Systems (AIS) and improving employee performance, using a moderator analysis approach. The context of the study is the increasing dependence of modern organizations on AIS for accurate financial data management and decision-making. However, the effectiveness of these systems can be influenced by various factors, including technological advancement and employee skills. The research methodology includes quantitative analysis, using survey data from various organizations in different sectors. Structural equation modeling (SEM) was applied to examine the moderating effect of IT on the relationship between AIS effectiveness and employee performance. The results of the study show a significant positive impact of IT on AIS effectiveness, leading to increased employee performance. These findings contribute to the literature by highlighting the importance of IT interventions in optimizing AIS functionality, thereby improving organizational efficiency and productivity. In conclusion, this study highlights the essential role of IT as a supporting tool to achieve higher levels of efficiency in accounting information systems and employee performance and highlights the need for continued technological advancement and employee training in the modern business environment.
The Role Information Technology in Increasing the Effectiveness Accounting Information Systems and Employee Performance Aoliyah Firasati; Fadhila Azzahra; Sausan Raihana Putri Junaedi; Amelia Evans; Muchlisina Madani; Fitra Putri Oganda
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 4 No. 2 (2024): October
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ijcitsm.v4i2.167

Abstract

This study explores the mportant role of Information Technology (IT) in enhancing the effectiveness of Accounting Information Systems (AIS) and improving employee performance, using a moderator analysis approach. The context of the study is the increasing dependence of modern organizations on AIS for accurate financial data management and decision-making. However, the effectiveness of these systems can be influenced by various factors, including technological advancement and employee skills. The research methodology includes quantitative analysis, using survey data from various organizations in different sectors. Structural equation modeling (SEM) was applied to examine the moderating effect of IT on the relationship between AIS effectiveness and employee performance. The results of the study show a significant positive impact of IT on AIS effectiveness, leading to increased employee performance. These findings contribute to the literature by highlighting the importance of IT interventions in optimizing AIS functionality, thereby improving organizational efficiency and productivity. In conclusion, this study highlights the essential role of IT as a supporting tool to achieve higher levels of efficiency in accounting information systems and employee performance and highlights the need for continued technological advancement and employee training in the modern business environment.
Optimization of Machine Learning Algorithms for Fraud Detection in E-Payment Systems Agung Rizky; Ahmad Gunawan; Maulana Arif Komara; Muchlisina Madani; Ethan Harris
CORISINTA Vol 2 No 1 (2025): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i1.68

Abstract

This study explores the optimization of machine learning algorithms for fraud detection in electronic payment (e-payment) systems. The rapid growth of e-payment platforms has introduced significant challenges in ensuring the security and integrity of financial transactions. Fraud detection plays a pivotal role in mitigating these risks, and the application of machine learning (ML) has emerged as a powerful tool to identify fraudulent activities. This research examines how Data Quality (DQ), Algorithm Selection (AS), and Optimization Techniques (OT) influence Model Performance (MP) and, subsequently, Fraud Detection Effectiveness (FDE). The study utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS 3 to analyze the relationships between these variables. The results demonstrate that high Data Quality significantly enhances Model Performance, while Algorithm Selection and Optimization Techniques also contribute positively, albeit to a lesser extent. The findings reveal that Model Performance plays a crucial mediating role between these factors and the effectiveness of fraud detection. Fraud Detection Effectiveness is found to be significantly impacted by Model Performance, suggesting that improving model accuracy and efficiency is essential for better fraud detection outcomes. Reliability and validity tests show strong internal consistency for all constructs, with Cronbach’s Alpha, Composite Reliability, and Average Variance Extracted (AVE) all reaching satisfactory levels. The study highlights the importance of data preprocessing, the careful selection of machine learning models, and optimization techniques in achieving high-performing fraud detection systems. The results provide valuable insights for the development of more robust and scalable fraud detection mechanisms in e-payment systems, contributing to the broader field of machine learning and cybersecurity. Future research could explore advanced techniques like deep learning and blockchain integration for further enhancement of fraud detection systems.
Co-Authors Agung Rizky Ahmad Gunawan Amelia Evans Aoliyah Firasati Ethan Harris Fadhila Azzahra Fitra Putri Oganda Maulana Arif Komara Sausan Raihana Putri Junaedi