( Department of Information Technology Faculty of Engineering and Information Technology Swiss German University )
Keywords: text mining,sentiment analysis,Business Intelligence,Business Analytic,Knowledge Discovery
Tweeting is one of the most common human activities around the world nowadays. Twitter is the name of the website that provides micro blogging services. Most people are tweeting whatever they feel. In this direction, the growth of mobile operators are also increasing, and competing to satisfy the customers, and the users of mobile operators are expressing their feelings about the mobile operators. The sentiment analysis then appears to analyze the mobile operator images from the customer side. This can be done by predicting the tweets from the mobile operator users by its sentiment. The training sets of data required to determine the sentiment of the testing data, and the training set is classified manually. This research is to propose an automatic sentiment for Indonesian mobile operators, which gathers insight from the customer side and the tweets are in Indonesian language and about several Indonesian mobile operators. The tweets for the training set are gathered in one month intervals. The accuracy of predicting the sentiment achieves 80%.