Analisis Sentimen Terhadap Tweets Samsung Indonesia Menggunakan Metode Support Vector Machine

Samsung as the world's leading smartphone company is a company that produces various types of technological devices. Technology as the driving force of human civilization is very important. However, in the course of time it is necessary to improve and evaluate gradually in order to satisfy needs properly and avoid undesirable things. Social media Twitter is an application that allows users to write about various topics and discuss current issues. Services are available to send tweets or re-tweets messages that have been shared. With the existence of Twitter this makes it easier for people to have an opinion. The opinion expressed by the public is a very valuable input and can be an instrument for evaluating. These opinions can be analyzed so that information can be obtained, but in practice, processing a text data requires an appropriate method so that the information generated can help many parties to support a decision or choice. Sentiment analysis is the classification of text documents into sentiment classes, such as positive and negative. This study aims to classify the community's tweets against the Samsung Indonesia company on Twitter social media using the Support Vector Machine method by using the data source from crawling tweets with samsungidas the reference keyword using the Twitter API. This research results that the number of tweets with negative sentiment is 13.37%, positive sentiment is 26.01%, and neutral sentiment is 60.60% tweets and the best model for classifying tweet data with SVM is to use data sharing by sharing training data by 80% and testing data by 20% and using value C = 1