TY  - JOUR
TI  - Detection of Credit Card Fraud in E-Commerce Using Data Mining
AB  - Credit card payment is one of the most preferred methods of e-commerce sites. Fraud orders are the biggest concerns for online shoppingsites. Fraud operations affect not only customers but also companies and banks. Hence, companies should be able to classify orders andtake measures against suspicious transactions. Classification is easier on the banking side because of more information about customers,but it is more difficult to determine this process on e-commerce sites. In this study, the actual order data of a private e-commerceenterprise has been examined and suspicious transactions are determined. First of all, all order data is analyzed and filtered. The bestvariables for classification are determined by variable selection algorithms. Afterwards, classification algorithms are applied andsuspicious orders are determined with 92% success rate. Naïve Bayesian, Decision Trees and Artificial Neural Network have been usedas comparative data mining methods.
AU  - Kırelli, Yasin
AU  - Arslankaya, Seher
AU  - ZEREN, MUHAMMED TAHA
DO  - 10.31590/ejosat.747399
PY  - 2020
JO  - Avrupa Bilim ve Teknoloji Dergisi
VL  - 0
IS  - 20
SN  - 2148-2683
SP  - 522
EP  - 529
DB  - TRDizin
UR  - http://search/yayin/detay/466163
ER  -