FAKE WEBSITE DETECTION USING SUPPORT VECTOR MACHINE LINEAR - Anisah
The trends of cybercrime through fake website make people try to design fake website detection system. Using a Statistical Learning Theory, we propose a mathematical model for detecting fake websites based on Plug-in Classier with Bayesian Statistics and Support Vector Machine Linear methods. This research uses fraud cue as training data which consist of internal links, webpage levels, and screenshoot of webpage header. These two methods applied to detect a number of legitimate and fake websites. The result shows that the Support Vector Machine Linear model has better website detection than the Plug-in Classier model.