A New Hybrid Decision Tree Algorithm with K-Nearest Neighbor for Cross Border Payment Risks

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Abstract

The technological advancement have aided in the dramatic growth in solving payment risks through the E-Commerce Applications. While blockchain technology was first developed to underpin Bitcoin, its potential uses outside that digital currency are also being investigated. Blockchain technology can be used to speed up the process in transactions, offered secured platform and resolve payment risks. Earlier to this development, the organization and companies are on huge demand of a finding a right solution to solve the payment risks, have to travel across border in search of it. This challenge is overcome with the technological advancement with blockchain. In this research, cross border based DTA-KNN model. KNN is utilized to perform the analysis in comparison with the neighbor countries and DTA performs choosing the right payment gateway through cross-borders. The proposed model is compared with the existing algorithms such as DTA and KNN for the entire processes. The results show that the hybrid model has achieved higher accuracy of 99.89%.

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APA

Fu, J., & Saad, N. H. M. (2022). A New Hybrid Decision Tree Algorithm with K-Nearest Neighbor for Cross Border Payment Risks. International Journal on Recent and Innovation Trends in Computing and Communication, 10(11), 181–190. https://doi.org/10.17762/ijritcc.v10i11.5805

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