Abstract
There are a lot of people facing scams and frauds each day throughout the year, everywhere around the world. While scam or a fraud can be a civil wrong or even a criminal wrong, a lot of the con artist are still at large. This is because scammers have honed their craft over years and years of trial and error. Currently, there are not enough or well-equipped platform as a place of reference where online shopper can go to when doing online shopping. Therefore, the proposed project have been developed which is FRAUD.MY: A crowdsourcing web application to detect scammer with Algolia and Google Extension Plugin. FRAUD.MY helps in providing online shoppers a place of reference when doing online shopping. With its search capabilities powered by Algolia Search Engine API, users can swiftly search any details regarding a scammer. FRAUD.MY is also equipped with a Google Extension Plugin where users can search without the hassle of going through FRAUD.MY itself. The developed web application received positive feedbacks after the evaluation with the functionality and usability testing was conducted. The network performance of FRAUD.MY was also evaluated in terms of page render time that was within 0.1535 milliseconds when using Digi. FRAUD.MY enables the users to access it anywhere at any time. For future works, it is recommended that FRAUD.MY integrates with the reports from other websites and from the authorities. On the other hand, enabling FRAUD.MY to search the approximate string matching will make it more efficient.
Metadata
Item Type: | Student Project |
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Creators: | Creators Email / ID Num. Syed Hedzer, Syed Muhamad Danial UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Computer software Q Science > QA Mathematics > Web-based user interfaces. User interfaces (Computer systems) T Technology > T Technology (General) |
Divisions: | Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences |
Keywords: | Web application; Detect scammers; Online shopping |
Date: | 2019 |
URI: | https://ir.uitm.edu.my/id/eprint/24101 |
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