Sentiment analysis using tweets data from Twitter of Indonesian's Capital City changes using classification method support vector machine

Abstract

Capital city in every country has an important role. One of them is for the central of government. A capital city is selected by considering many aspects. These include location which is in the middle of the country, and history which was happened before. On the middle of 2019, Indonesian's President announced that Indonesian's capital city will be shifted from Jakarta to East Kalimantan. The statement makes a lot of public opinions especially in social media Twitter. The opinions can be used for sentiment analysis. This research aims to classify the information of public sentiments about Indonesian's capital city changes. The classification divided by two class which are positive sentiments and negative sentiments. The classification method that used in this sentiment analysis research is Support Vector Machine (SVM) with three function method, which are linear function, Radial Basis Function (RBF), and sigmoid function. The process include text mining, text preprocessing, analyze using SVM, data classification, and visualization. From the result of classification, linear function is the best function on this research with the accuracy value is 96,93% with 97,81% specificity value and 95% sensitivity value.