Crime Rate Detection Based on Text Mining on Social Media Using Logistic Regression Algorithm

Social media recently are very populer in Indonesia and in the world. Luckly, this platform may express their opinion and emotion even other party especially reseacher mostly use this opportunity to find any solution for any case likely competitive business, decisions maker, and possible analitics and predictive support system. In this case our analysis is content on Twitter and Facebook which user often posted information about the crime which matters need police attention. Therefore our purpose is detection of crime rate on social media to find pattern trend of tweet number crime. This work used text mining approach for classification of tweet and post content text into 10 class of crime. The Algorithm used for classifier are Logistic Reggression, Naive Buyes, Support Vector Machine (SVM) and Decission Tree, from all the algorithm used, Logistic regression give the best accuracy of 90%