Accuracy Analysis of Data Fraud Detection for Company Transactions Using Two-Layered Feed Forward Neural Network Approach Compared with Random Forest

Abstract

Aim: To find accuracy of data fraud detection for company transactions using two-layered feed forward Neural Network approaches compared with Random Forest. Materials and methods: Number of groups is 2. Group 1 - Two-layered feed forward Neural Network, and Group 2 - Random Forest. Results: The accuracy of the innovative feed forward Neural Network method is 83.4% and Random Forest is 85.5%. The accuracy of the Random Forest algorithm appears to be a slight increase. Conclusion: Random Forest algorithm finds the fraud detection appearance to be better accuracy than the feed forward Neural Network.