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All Journal International Journal of Intelligent Systems and Applications in Engineering
Toraman, Taner
Advanced Technology and Science (ATScience)
Computer Science & IT

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Fraud Detection on Financial Statements Using Data Mining Techniques Sorkun, Murat Cihan; Toraman, Taner
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 3 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017531428

Abstract

This study explores the use of data mining methods to detect fraud for on e-ledgers through financial statements. For this purpose, data set were produced by rule-based control application using 72 sample e-ledger and error percentages were calculated and labeled. The financial statements created from the labeled e-ledgers were trained by different data mining methods on 9 distinguishing features. In the training process, Linear Regression, Artificial Neural Networks, K-Nearest Neighbor algorithm, Support Vector Machine, Decision Stump, M5P Tree, J48 Tree, Random Forest and Decision Table were used. The results obtained are compared and interpreted.
Co-Authors Sorkun, Murat Cihan