en مديريت ورزشی و شاخه‌های وابسته بدان Sport Management and its related branches مقاله اصیل Original Article <div style="text-align: justify;"><strong>Background. </strong>Combining a One-Class Support Vector Machine (OCSVM) with a Convolutional Neural Network (CNN) is presented as a novel technique for detecting fraud in Enterprise Resource Planning (ERP) systems.<br> <strong>Objectives. </strong>The objective of this research is to develop a technique for detecting fraud in Enterprise Resource Planning (ERP) systems by combining a One-Class Support Vector Machine (OCSVM) with a Convolutional Neural Network (CNN), suitable for the Spor Istanbul ERP system.<br> <strong>Methods. </strong>This study examines the ERP system utilized by Spor Istanbul, the largest sports enterprise in Turkey, as a case study. The study utilizes a custom database of web-based program files to create a dataset of benign and malicious JavaScript applications. Firstly, the text and control flow graph of the program is analyzed. Secondly, the OCSVM method is applied as an outlier detection technique, and CNN is used as a classifier.<br> <strong>Results. </strong>The experimental results indicate that the proposed OCSVM-CNN approach achieves higher accuracy (96.78%) in detecting malicious scripts compared to using only CNN (94.8%).<br> <strong>Conclusion. </strong>The research contributes to the development of multi-layered ERP software architecture with AI decision support, improving fraud detection in ERP systems.</div> Enterprise Resource Planning, Intelligent ERP, Forecasting, Demand Prediction, Decision Support System, Artificial Neural Networks, Cellular Neural Networks, Multi-Layered Software Architecture 0 0 http://aassjournal.com/browse.php?a_code=A-11-2079-2&slc_lang=en&sid=1 Emrah Arslan emraha@stu.aydin.edu.tr 100319475328460013098 100319475328460013098 Yes Department of Computer Engineering, Faculty of Engineering, Istanbul Aydın University, Istanbul, Turkey Ali Güneş aligunes@aydin.edu.tr 100319475328460013099 100319475328460013099 No Department of Computer Engineering, Faculty of Engineering, Istanbul Aydın University, Istanbul, Turkey