Sentiment Analysis Pada Teks Bahasa Indonesia Menggunakan Support Vector Machine (SVM) Dan K-Nearest Neighbor (K-NN)

DAFTAR PUSTAKA

Abbasi, Ahmed. Zhang, Zhu & Chun, Hsinchun. 2008. A Statistical Learning Based System
for Fake Website Detection. The Workshop on Secure Knowledge Management.
Dallas: Texas.
Auria, Laura. A, Moro, Rouslan. 2008. Support Vector Machines (SVM) as a Technique for
Solvency Analysis. Berlin: Deutsches Institut für Wirtschaftsforschung
Barber, I. 2009. Simple Search : The Vector Space Model. (Online). http:// phpir.com/simplesearch-the-vector-space-model (10 Nov 2014)
Bo, Pang & Lilian, Lee. 2008. Opinion Mining and Sentiment Analysis, Foundations and
Trends in Information Retrieval, Volume 2, no. Issue 1-2, pp. 1-135.
Bridge, C. 2011. Unstructured Data and the 80 Percent Rule. (Online)
http://www.clarabridge.com/default.aspx?tabid=137&ModuleID=635&ArticleID
=551 (5 Nov 2013).
Cawley, G, C. 2006. Leave-one-out cross-validation based model selection criteria for
weighted LS-SVMs. Proceedings of the IEEE/INNS International Joint Conference
on Neural Networks (IJCNN-06),Vancouver, BC, Canada, pp. 1661–1668
Colas, F & Brazdil, P. 2006. Comparison of SVM and Some Older Classification Algorithms
in Text Classification Tasks. Artificial Intelligence In Theory and Practice, IFIP In
International Federation for Information Processing, (Boston: Springer), Volume
217, pp. 169-178.
Cortes, C. & Vapnik, V. 1995. Support-Vector Networks Machine Learning, 20. (Online).

http://www.springerlink.com/content/k238jx04hm87j80g/. (8 Nov 2013).
Darujati, Cahyo. 2010. Perbandingan Klasifikasi Dokumen Teks Menggunakan Metode
Naïve
Bayes Dengan K-Nearest Neighbor. Jurnal Link (Information Retrieval). Volume 13.
No.1, pp. 2-9
Manning, D, Christopher. Raghavan, Prabhakar & Schütze, Hinrich. 2009. An Introduction to
Information Retrieval. Cambridge: Cambridge University Press.
Feldman. J.A. 2004. Computational cognitive linguistics. Proc. 20th Intl. Conf. on
Computational Linguistics, Morristown, NJ: Association for Computational
Linguistics, pp. 1114-1118.
Ganjisaffar, Yasser. 2013. crawler4j : open source web crawler for java.(Online).
https://code.google.com/p/crawler4j/ (1 Maret 2014)

Universitas Sumatera Utara

Gorunescu, Florin. 2011. Data Mining: Concepts, Models and Techniques. Computational
Intelligence and Complexity. (Verlag Berlin Heidelberg-Springer), Volume 12.
pp. 1-43.
Guo, Gongde. Wang, Hui. Bell, David. Bi, Yaxin. & Greer, Kieran. 2001. Using K-NN
Model-based Approach for Automatic Text Categorization. Northem Ireland : School

of Computing and Mathematics
Han, qi. Guo, junfei & Schuetze, hinrich. 2013. Combining an SVM Classifier and Character
N-gram Language Models for Sentiment Analysis on Twitter Text. Association for
Computational Linguistics: Human Language Technologies.
Hedley, Jonathan. 2013. jsoup 1.7.4-Snapshot API : Open Source Java HTML parser that
makes sense of real-world HTML soup. (Online). http://jsoup.org/apidocs/ (13 Mei
2014)
Ian, H,Witten. Frank, Eibe & Mark A, Hall. 2011. Data mining: Practical Machine Learning
Tools and Techniques 3rd Edition. Elsevier.
Jason D. M. Rennie & Ryan Rifkin. Improving Multiclass Text Classification with
the Support Vector Machine. (Online). http://www.ai.mit.edu. (1 Maret 2014)
Jurgens, David. 2009. S-Space : free software. (Online). http://github.com. (13 Mei 2014)
Karatzoglou, Alexandros. Smola, Alexandros. Hornik, Kurtand & Zeileis, Achim. 2004.
kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software.
Volume 11. pp 1-20.
Khushboo, N, Trivedi. Swati, K. Vekariya. & Prof. Shailendra, Mishra. 2012. Mining of
Sentences Level Opinion Using Supervised Term Weighted Approach of Naïve
Bayesian Algorithm. int. J. Computer Technology & Applications, Volume 3, pp. 987991.
Kumar, M. A. & Gopal, M. 2009. Least Squares Twin Support Vector Machines for Pattern
Classification. Expert Systems with Applications, Volume 36, pp. 7535–7543.

Li, Rong. Wang, Hua-Ning. He, Han. Cui, Yan-Mei & Du, Zhan-Le. 2006. Support Vector
Machine combined with K-Nearest Neighbors for Solar Flare Forecasting. Chinese
Academy of Sciences. Volume 7, pp. 441-447.
Liu, Bing. 2010. Sentiment Analysis and Subjectivity, in Handbook of Natural Language
Processing Second Edition, (editors: N. Indurkhya and F. J. Damerau). Department of
Computer Science : University of Illinois at Chicago

Universitas Sumatera Utara

Nazief, B. A. A. & Adriani, M. 1996. Confix Stripping: Approach to Stemming Algorithm
for Bahasa Indonesia. Internal Publication, Faculty of Computer Science, Jakarta:
University of Indonesia.
Nurfalah, Adiyasa. 2011. Analisis Sentimen Pada Opini Berbahasa Indonesia Menggunakan
Pendekatan Lexicon-Based. Matakuliah Data Mining Lanjut. Bandung: Fakultas
Pascasarjana Institut Teknologi Telkom.
Sumartini, Ni Wayan. 2011. Text Mining Classifier dengan Metode Naïve Bayes dan
Support Vector Machines untuk Sentiment Analysis. Tesis. Universitas Udayana.
Tan, P. N., Steinbach, M. & Kumar, V. 2006. Introduction to Data Mining. Boston : Pearson
Addison Wesley
Vinodhini, G. Chandrasekaran, RM. 2012. Sentiment Analysis and Opinion Mining: A

Survey. International Journal of Advanced Research in Computer Science and
Software Engineering: pp. 283-293.
Wulandini, F. & Nugroho, A. N. 2009. Text Classification Using Support Vector Machine for
Webmining Based Spation Temporal Analysis of the Spread of Tropical Diseases.
International Conference on Rural Information and Communication Technology
2009.
(Online) 189-192. http://asnugroho.net/papers/rict2009_textclassification.pdf (5 Nov
2013).
Zee-Jing, Chung & Hsien-Wu, Chung. 2004. Multi modal Emotion Recognition from Speech
and Text. The Association for Computational Linguistics and Chinese Language
Processing: pp. 45-62.

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