Abstract
Twitter is one type of social media that is often used. Users use Twitter to convey their tweet to the general public. The number of Twitter users has reached 330 million people worldwide. Besides that, in Twitter there are tweets that can be sentiments. Sentiment itself can be defined as policy, opinion, logic, or mud, etc. Therefore, sentiment analysis is determining the polarity or type of opinion in a predetermined text or subject. NLP (Natural Language Processing) technique is used to support the beginning of a text. The technique used in an analysis is tokenization sentiment, elimination of stop words, and stemming. This study focuses on developing sentiment analysis using lexicons and multiplication polarity. Accuracy results are still smaller than using machine learning. Therefore, this lexicon needs to be improved in terms of its semantics.
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