To perform the credit card fraud detection based on the approved and fraudster users using Artificial Neural Network algorithm compared with Support Vector Machine algorithm. Materials and Method: Credit card fraud detection is performed using Artificial Neural Network algorithm (N=1780) and Support Vector Machine algorithm (N=1780). The credit cards dataset was trained to Artificial Neural Network algorithm and Support Vector Machine algorithm and tested to detect the credit card fraudulent. Optimal value is identified when the split size of training and test dataset used in the Artificial Neural Network algorithm is 30% and Support Vector Machine 70%. Results and Discussion: Artificial Neural Network achieved significantly better accuracy rate (98.57) in comparison with Support Vector Machine (96.78%) and attained the significance value of p = 0.036. Conclusion: Artificial Neural Network achieved significantly better prediction rate for credit card fraud detection than Support Vector Machine.
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