On the Development of Smart-Watch Detection Using C 5.0 and S 5.24.1 Algorithms
Philip Seths Onyekachi., Amanze Bethran Chibuike., Igbe Chukwudi M
Abstract
Smart-Watch as an emerging IoT solution in order to recognize human activities with respect to payment transactions. To implement this, a web application was developed specifically for payment transactions. The Smart-Watch is embedded within the transaction platform to monitor transactions on the IoT platform, and detect when a transaction is suspected to be a fraudulent. For the purpose of classifying transactions, we considered the C5.0 algorithm and S5.24.1 to present reliability of the Smart-Watch. The result from the software developed was tested using Confusion Matrix with a dataset of 100 transactions. The result obtained shows almost 93% of accuracy in detecting fraud using Smart-Watch. The Smart-Watch system has a high accuracy, and it will be a reliable system and also a profitable investment if put into action in the business world.
Keywords
References
Panigrahi, S., Kundu, A., Sural, S. and Majumdar, A. K. (2019) “Credit card fraud detection: a
fusion approach using dempstershafer theory and bayesian learning,” Information Fusion,
vol. 10, no. 4, pp. 354–363.
Rani, S. L. (2018) Smart Banking Using IoT. Computer Science & Engineering Department Prof
Ram Meghe College of Engineering and Management, Badnera Amravati, India
Bhalinder, K., Shivinder, K. (2020) Overview Of Intelligent Systems. International Journal of
Computing & Business Research ISSN (Online): 2229-6166
