In recent years, fake news has drawn attention among society especially social media users. The growing use of social media as a platform to get the latest news and information has enabled the rapid spread of fake news. Fake news content is never true and left the readers believing what they have read are true and confusing. The spreading of fake news can give negative impacts on individuals and society especially fake news in political events. The challenge is that the human fact-checkers cannot keep up with the amount of misinformation and the speed at which it spreads. One of the reasons for this is that fact-checking is an intellectually demanding, laborious, and time-consuming process. This challenge creates an opportunity for automated fact-checking systems. On the other hand, fact-checking technology is clearly falling behind, as there is simply no existing system that truly does automated fact-checking. The proposed solution is to develop a real time fact-checking system in mission to provide transparency and accuracy in detecting fake news. This system will apply classification models to classify the facts. Fake News Detection System is web application, where it also provide visualization on fake news. The user site is able to view the news content that already have been checked whether it is fact or hoax and analytic dashboard to see graphical information. For now, the system is focus on more political issue as the society have more eyes on this.