ANALISIS SENTIMEN PADA TWITTER MENGGUNAKAN METODE MAXIMUM ENTROPY DAN SUPPORT VECTOR MACHINE

CINDO, MONA and Rini, Dian Palupi and Ermatita, Ermatita (2019) ANALISIS SENTIMEN PADA TWITTER MENGGUNAKAN METODE MAXIMUM ENTROPY DAN SUPPORT VECTOR MACHINE. Master thesis, Sriwijaya University.

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Abstract

Social media such as Twitter are often used by users to give opinions about the quality of products they use, express their emotions every day and some companies such as airlines use to gain competitive advantage by continuing to improve service and experience of service users by using twitter to become an important source for tracking sentiment analysis. Sentiment analysis is done to see opinions or tendencies of opinion on a problem. This study uses two types of datasets, namely public opinion data and airline opinion data to test the best features and methods. Feature extraction is expected to improve the accuracy of sentiment analysis. To get the best results this research uses two methods, namely maximum entropy and support vector machine as a comparison. The best results are found in the maximum entropy method which has an average accuracy of 85.8 % for the general opinion dataset while in the airline's opinion dataset the accuracy reaches 92.6%.

Item Type:	Thesis (Master)
Uncontrolled Keywords:	Twitter, Support Vector Machine, Maximum Entropy, Feature Extraction
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Divisions:	09-Faculty of Computer Science > 55101-Informatics (S2)
Depositing User:	Users 1700 not found.
Date Deposited:	04 Sep 2019 09:13
Last Modified:	04 Sep 2019 09:13
URI:	http://repository.unsri.ac.id/id/eprint/6272

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