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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 6, 2022.
Abstract: The purpose of this project is to prevent cases of fraud in e-commerce of purchase and sale from person to person through social networks. For the development of the research work, the Scrum methodology was used to allow the project to be carried out in an agile and flexible way, adapting to the changes that could arise along the way. The technological tools that made this project possible were SQL Server, C++, Visual Studio and Marvel app, the latter for prototype design. In addition, there was the support of an artificial intelligence software known as Optical Character Recognition that allowed the document recognition process to be completed. The social network Facebook was also relevant for the development process since the data set for the training of the system was obtained from there, guaranteeing its functionality. The results obtained benefit both parties, sellers/suppliers and consumers, reducing the impact of fraud cases and guaranteeing safer online operations. In addition, a validation was carried out by experts in the development of web applications, taking usability, feasibility, scalability, innovation, and technology as criteria. Obtaining as a result the approval in all its criteria; with the total mean value of 2.76.
Edwin Kcomt Ponce, Katherine Escobedo Sanchez and Laberiano Andrade-Arenas, “Implementation of a Web System: Prevent Fraud Cases in Electronic Transactions” International Journal of Advanced Computer Science and Applications(IJACSA), 13(6), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01306102
@article{Ponce2022,
title = {Implementation of a Web System: Prevent Fraud Cases in Electronic Transactions},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01306102},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01306102},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {6},
author = {Edwin Kcomt Ponce and Katherine Escobedo Sanchez and Laberiano Andrade-Arenas}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.