  The rapid growth of the e-commerce market in Indonesia, making various
e-commerce companies appear and there has been high competition among them.
Marketing intelligence is an important activity to measure competitive
position. One element of marketing intelligence is to assess customer
satisfaction. Many Indonesian customers express their sense of satisfaction or
dissatisfaction towards the company through social media. Hence, using social
media data provides a new practical way to measure marketing intelligence
effort. This research performs sentiment analysis using the naive bayes
classifier classification method with TF-IDF weighting. We compare the
sentiments towards of top-3 e-commerce sites visited companies, are Bukalapak,
Tokopedia, and Elevenia. We use Twitter data for sentiment analysis because
it's faster, cheaper, and easier from both the customer and the researcher
side. The purpose of this research is to find out how to process the huge
customer sentiment Twitter to become useful information for the e-commerce
company, and which of those top-3 e-commerce companies has the highest level of
customer satisfaction. The experiment results show the method can be used to
classify customer sentiments in social media Twitter automatically and Elevenia
is the highest e-commerce with customer satisfaction.
