Analisis Opini Terhadap Fitur Smartphone Pada Ulasan Website Berbahasa Indonesia

Doni Setyawan(1*), Edi Winarko(2)

(1) Universitas Widya Dharma Klaten
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author


 Through online stores, consumers can give an opinion of a product, one of the best-selling products is smartphone. Their opinions become valuable and can be worthwhile to know the advantages or disadvantages of products based on the user’s experience. Therefore, in order to utilize the data of customers' opinions, it is necessary to create a system that automatically performs mining and summarizing opinions on smartphone product. The system consist of five parts: data collection, preprocessing review, feature mining, analysis of opinions and then visualize the results. Data collection is taking data reviews website using web scraping, preprocessing review is for cleaning data reviews. Feature mining stage  will find features in the reviews with apriori algorithm to produce frequent item set, then analyze the opinion using lexicon based, language rule and score function. The result will be shown in graphical form. From the testing of  feature mining obtained average recall score at 0.63 and precision at 0.72. It depends on good or bad quality of reviews. The results of testing accuracy opinion analysis shows high value with accuracy 81.76 %. The technique showed good results with opinion data which is labeled, using language rule and the implementation of score function.


smartphone, review, frequent itemset, linguistic rule, opinion analysis

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[1] Berliyanto, 2015, Profil Pengguna Internet di Indonesia Tahun 2015,, diakses 3 Desember 2015
[2] Prabancono, 2015, Wow Pengguna Smartphone di Indonesia Capai 55 Juta Orang,, 20 September 2015, diakses 3 Desember 2015..
[3] Liu, B., 2010, Handbook of Natural Language Processing, chapter Sentiment Analysis and Analysis, 2nd Edition.
[4] Hamzah, A., 2012, Klasifikasi Teks Dengan Naive Bayes Classifier (NBC) Untuk Pengelompokan Teks Berita dan Akademis, ISSN:1979-911I, vol. 3, 2012.
[5] Shoukry, A. M., 2013, Arabic sentence level sentiment analysis, Dissertation, Department of Computer Science and Engineering, The American University in Cairo.
[6] Htay, S. dan Lynn, K.T., Extracting Product Features and Opinion Words

[7] Komansilan, E., 2012, Penambangan Opini Pada Situs Review Film Berbahasa Indonesia, Tesis, Jurusan Ilmu-ilmu Komputer FMIPA UGM, Yogyakarta.
[8] Hu, M., dan Liu, B. 2004. Mining and Summarizing Customer Reviews. Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Seattle, Washington, USA, Agustus
[9] Ding, X., Liu, B. dan Yu, P. 2008. A holistic lexicon-based approach to opinion mining. In Proceedings of the Conference on Web Search and Web Data Mining (WSDM-2008).
[10 Kohavi, R., dan Provost, F., 1998, On Applied Research in Machine Learning. In Editorial for the Special Issue on Applications of Machine Learning and the Knowledge Discovery Process, Columbia University, New York, Volume 30.


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