A SURVEY OF SENTIMENT ANALYSIS USING SENTIWORDNET ON BAHASA INDONESIA
DOI:
https://doi.org/10.47111/jti.v12i2.534Keywords:
user opinion, Indonesian, sentiwordnet, sentiment analysisAbstract
High internet usage in Indonesia brings a number of data user opinions. User
opinion data can be processed into information that is useful for decision making, data
searching and researching for production and marketing strategies. This research
conducted a survey on some Indonesian Sentiment Analysis research articles. Some of these
studies have different topics and data sources, butuse Sentiwordnet as a lexical database.
The results of this survey show the performance of Sentiwordnet can improve classification
accuracy in the Sentiment analysis system for Indonesian text.
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References
[1] Endang Wahyu Pamungkas, Divi Galih Prasetyo Putri, An Experimental Study of Lexicon-based Sentiment Analysis on Bahasa Indonesia, 2016. Proceedings of 6th Annual Engineering Seminar (InAES), Yogyakarta, Indonesia
[2] Lailiyah M, Sumpeno S, Purnama I.K.E, Sentiment Analysis of Public Complaint Using Lexical Resources Between Indonesian Sentiment and Sentiwordnet, 2017.Proceedings of International Seminar on Intelligent Technology and Its Application 2017, IEEE
[3] Edwin Lunando, Ayu Purwarianti, 2013, Indonesian Social Media Sentiment Analysis with Sarcasm Detection, 2013. Jurnal Sarjana Institut Teknolodi Bandung Bidang Teknik Elektro dan Informatika, Juni 2013
[4] Anju Rose G. Punneliparambi, Latest Trends in Sentiment Analysis-A Surver, 2017. International Journal of Computer Science and Engineering Communication.
[5]Stefano Baccianella, Andrea Esuli, Fabrizio Sebastiani, Sentiwordnet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. 2010, Proceedings of the International Conference on Language Resources and Evaluation, LREC 2010, 17-23 May 2010, Valletta, Malta
[2] Lailiyah M, Sumpeno S, Purnama I.K.E, Sentiment Analysis of Public Complaint Using Lexical Resources Between Indonesian Sentiment and Sentiwordnet, 2017.Proceedings of International Seminar on Intelligent Technology and Its Application 2017, IEEE
[3] Edwin Lunando, Ayu Purwarianti, 2013, Indonesian Social Media Sentiment Analysis with Sarcasm Detection, 2013. Jurnal Sarjana Institut Teknolodi Bandung Bidang Teknik Elektro dan Informatika, Juni 2013
[4] Anju Rose G. Punneliparambi, Latest Trends in Sentiment Analysis-A Surver, 2017. International Journal of Computer Science and Engineering Communication.
[5]Stefano Baccianella, Andrea Esuli, Fabrizio Sebastiani, Sentiwordnet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. 2010, Proceedings of the International Conference on Language Resources and Evaluation, LREC 2010, 17-23 May 2010, Valletta, Malta
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Published
2018-08-01
