Clustering Artikel Web Kesehatan Dengan Algoritma Self Organizing Maps
49
DAFTAR PUSTAKA
Adriani, M., & Nazief, B. 1996. Confix-Stripping: Approach to Stemming Algorithm
for Bahasa Indonesia . Faculty of Computer Science University of Indonesia.
Adriani, M., Asian, J., Nazief, B., Tahaghoghi, S.M.M., & Williams H.E. 2007.
Stemming Indonesian: A Confix-Stripping Approach. Journal ACM Transactions
on Asian Language Information Processing 6(4): 1-33.
Agusta, L. 2009. Perbandingan Algoritma Stemming Porter Dengan Algoritma Nazief
& Adriani Untuk Stemming Artikel Teks Bahasa Indonesia. Prosiding Konferensi
Nasional Sistem dan Informatika 2009, pp. 196-201.
Alodokter.
2016.
Alodokter
Daftar
Penyakit.
http://www.alodokter.com/penyakit-a-z (Diakses 2 Agustus 2016)
(Online)
Al-Marghilani, A., Zedan, H. & Ayesh, A. 2008. Text Mining Based on Self
Organizing Map Method for Arabic-English Documents. Proceedings of the
Nineteenth Midwest Artificial Intelligence and Cognitive Science Conference
(MAICS 2008), pp. 174-181.
Amalia, Gunawan, D., Najwan, A., & Meirina, F. 2016. Focused Web Crawler for the
Acquisition of Health Articles. Proceeding of International Conference on Data
and Software Engineering, pp. 47-52.
Ambarwati & Winarko, E. 2014. Pengelompokan Berita Indonesia Berdasarkan
Histogram Kata Menggunakan Self-Organizing Map. Indonesian Journal of
Computing and Cybernetics Systems 8(1): 101-110.
Berry, W.M. & Kogan, J. 2010. Text Mining: Applications and Theory. Wiley: Padstow.
Gatial, E., Balogh, Z., Laclavik, M., Ciglan, M. and Hluchy, L. Focused Web Crawling
Mechanism based on Page Relevance. Proceedings Information Technologies Applications and Theory, Peter Vojtas (Ed.), pp.41-46.
Gutwin, C., Paynter, G., Witten, I., Nevill-Manning, C., and Frank, E. 1999. Improving
Browsing in Digital Libraries with Keyphrase Indexes. Decision Support Systems,
27: 81–104.
Hulth, A., & Megyesi, B.B. 2006. A Study on Automatically Extracted Keywords in
Text Categorization. Proceedings of the 21st International Conference on
Computational Linguistics and the 44th Annual Meeting of the Association for
Computational Linguistics, pp. 537-544.
Universitas Sumatera Utara
50
Husni, Negara, Y.D.P., & Syarief. M. 2015. Clusterisasi Dokumen Web (Berita) Bahasa
Indonesia Menggunakan Algoritma K-Means. Jurnal SimanteC 4(3): 159-166.
Ikatan Dokter Anak Indonesia, 2015. IDAI - Public
http://www.idai.or.id/artikel (Diakses 11 Juli 2016).
Articles.
(Online)
Kateglo, 2016. Kateglo ~ Kamus, tesaurus, dan glosarium bahasa Indonesia. (Online)
http://www.kateglo.com/ (Diakses 1 Agustus 2016).
Kementerian Kesehatan Republik Indonesia, 2013. Kementerian Kesehatan Republik
Indonesia
Kamus.
(Online)
http://www.depkes.go.id/folder/view/full-content/structure-kamus.html (Diakses
21 Juli 2016)
Kohonen, T. 1995. Self-Organizing Maps. Springer: Berlin.
Prasetyo, E. 2012. Konsep dan Aplikasi Menggunakan MATLAB. Andi: Yogyakarta.
Robertson, S., 2004. Understanding Inverse Document Frequency: On theoretical
arguments for IDF. Journal of Documentation 60(5): 503-520.
Samodra, Sumpeno & Hariadi. 2009. Klasifikasi Dokumen Teks Berbahasa Indonesia
dengan Menggunakan Naïve Bayes. Seminar Nasional Electrical, Informatics,
and IT Education 2009, pp. B1-71 – B1-74.
Suryaningsih, V. 2015. Clustering Dokumen Menggunakan Algoritma Self Organizing
Maps. Skripsi. Universitas Negeri Sebelas Maret.
Tala, F.Z. 2003. A Study of Stemming Effects on Information Retrieval in Bahasa
Indonesia . Tesis. Institute for Logic, Languange and Computation. Universiteti
van Amsterdam the Netherlands.
Turney, P. 1999. Learning to Extract Keyphrases from Text. National Research Council
Canada, Institute for Information Technology, Technical Report ERB-1057
Vijayarani, S., & Janani, R. 2016. Text Mining: Open Source Tokenization Tools – An
Analysis. Advanced Computational Intelligence: An International Journal (ACII)
3(1): 37-47.
Yang, H.-C., Chen, D.-W., Lee, & C.-H. 2007. Mining Multilingual Texts Using
Growing Hierarchical Self-Organizing Maps. Proceedings of the Sixth
International Conference on Machine Learning and Cybernetics 2007, pp. 22632268.
Yusuf, A. & Priambadh, T. 2013. Support Vector Machines Yang Didukung K-Means
Clustering Dalam Klasifikasi Dokumen. Jurnal Ilmiah Teknologi Informasi
11(1): 13-16.
Universitas Sumatera Utara
DAFTAR PUSTAKA
Adriani, M., & Nazief, B. 1996. Confix-Stripping: Approach to Stemming Algorithm
for Bahasa Indonesia . Faculty of Computer Science University of Indonesia.
Adriani, M., Asian, J., Nazief, B., Tahaghoghi, S.M.M., & Williams H.E. 2007.
Stemming Indonesian: A Confix-Stripping Approach. Journal ACM Transactions
on Asian Language Information Processing 6(4): 1-33.
Agusta, L. 2009. Perbandingan Algoritma Stemming Porter Dengan Algoritma Nazief
& Adriani Untuk Stemming Artikel Teks Bahasa Indonesia. Prosiding Konferensi
Nasional Sistem dan Informatika 2009, pp. 196-201.
Alodokter.
2016.
Alodokter
Daftar
Penyakit.
http://www.alodokter.com/penyakit-a-z (Diakses 2 Agustus 2016)
(Online)
Al-Marghilani, A., Zedan, H. & Ayesh, A. 2008. Text Mining Based on Self
Organizing Map Method for Arabic-English Documents. Proceedings of the
Nineteenth Midwest Artificial Intelligence and Cognitive Science Conference
(MAICS 2008), pp. 174-181.
Amalia, Gunawan, D., Najwan, A., & Meirina, F. 2016. Focused Web Crawler for the
Acquisition of Health Articles. Proceeding of International Conference on Data
and Software Engineering, pp. 47-52.
Ambarwati & Winarko, E. 2014. Pengelompokan Berita Indonesia Berdasarkan
Histogram Kata Menggunakan Self-Organizing Map. Indonesian Journal of
Computing and Cybernetics Systems 8(1): 101-110.
Berry, W.M. & Kogan, J. 2010. Text Mining: Applications and Theory. Wiley: Padstow.
Gatial, E., Balogh, Z., Laclavik, M., Ciglan, M. and Hluchy, L. Focused Web Crawling
Mechanism based on Page Relevance. Proceedings Information Technologies Applications and Theory, Peter Vojtas (Ed.), pp.41-46.
Gutwin, C., Paynter, G., Witten, I., Nevill-Manning, C., and Frank, E. 1999. Improving
Browsing in Digital Libraries with Keyphrase Indexes. Decision Support Systems,
27: 81–104.
Hulth, A., & Megyesi, B.B. 2006. A Study on Automatically Extracted Keywords in
Text Categorization. Proceedings of the 21st International Conference on
Computational Linguistics and the 44th Annual Meeting of the Association for
Computational Linguistics, pp. 537-544.
Universitas Sumatera Utara
50
Husni, Negara, Y.D.P., & Syarief. M. 2015. Clusterisasi Dokumen Web (Berita) Bahasa
Indonesia Menggunakan Algoritma K-Means. Jurnal SimanteC 4(3): 159-166.
Ikatan Dokter Anak Indonesia, 2015. IDAI - Public
http://www.idai.or.id/artikel (Diakses 11 Juli 2016).
Articles.
(Online)
Kateglo, 2016. Kateglo ~ Kamus, tesaurus, dan glosarium bahasa Indonesia. (Online)
http://www.kateglo.com/ (Diakses 1 Agustus 2016).
Kementerian Kesehatan Republik Indonesia, 2013. Kementerian Kesehatan Republik
Indonesia
Kamus.
(Online)
http://www.depkes.go.id/folder/view/full-content/structure-kamus.html (Diakses
21 Juli 2016)
Kohonen, T. 1995. Self-Organizing Maps. Springer: Berlin.
Prasetyo, E. 2012. Konsep dan Aplikasi Menggunakan MATLAB. Andi: Yogyakarta.
Robertson, S., 2004. Understanding Inverse Document Frequency: On theoretical
arguments for IDF. Journal of Documentation 60(5): 503-520.
Samodra, Sumpeno & Hariadi. 2009. Klasifikasi Dokumen Teks Berbahasa Indonesia
dengan Menggunakan Naïve Bayes. Seminar Nasional Electrical, Informatics,
and IT Education 2009, pp. B1-71 – B1-74.
Suryaningsih, V. 2015. Clustering Dokumen Menggunakan Algoritma Self Organizing
Maps. Skripsi. Universitas Negeri Sebelas Maret.
Tala, F.Z. 2003. A Study of Stemming Effects on Information Retrieval in Bahasa
Indonesia . Tesis. Institute for Logic, Languange and Computation. Universiteti
van Amsterdam the Netherlands.
Turney, P. 1999. Learning to Extract Keyphrases from Text. National Research Council
Canada, Institute for Information Technology, Technical Report ERB-1057
Vijayarani, S., & Janani, R. 2016. Text Mining: Open Source Tokenization Tools – An
Analysis. Advanced Computational Intelligence: An International Journal (ACII)
3(1): 37-47.
Yang, H.-C., Chen, D.-W., Lee, & C.-H. 2007. Mining Multilingual Texts Using
Growing Hierarchical Self-Organizing Maps. Proceedings of the Sixth
International Conference on Machine Learning and Cybernetics 2007, pp. 22632268.
Yusuf, A. & Priambadh, T. 2013. Support Vector Machines Yang Didukung K-Means
Clustering Dalam Klasifikasi Dokumen. Jurnal Ilmiah Teknologi Informasi
11(1): 13-16.
Universitas Sumatera Utara