Universitas Gadjah Mada, [26] V. K. Singh, R. Piryani, A. Uddin, P. Waila, and Marisha, Sentiment analysis of textual reviews; Evaluating

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1 DAFTAR PUSTAKA [1] A. Na im and J. Hartono, The Effect Of Antitrust Investigations On The Management Of Earnings: A Further Empirical Test Of Political Cost Hypothesis, Kelola, vol. 5, no. 1996, [2] E. Elisabeth Sinaga, K. Titiek, and Y. Mirza, GOLONGAN PUTIH (GOLPUT) DALAM PEMILU LEGISLATIF 2009 DI KOTA BENGKULU, ut, Fakultas Ilmu Sosial Dan Ilmu Politik UNIB, [3] M. Yahya, SEJARAH PERKEMBANGAN DEMOKRASI, KARYA Ilm. Mhs. S1 Sist. Inf., vol. 0, no. 0, Nov [4] Pesta Rakyat di pelantikan Jokowi-Jusuf Kalla, merdeka.com. [Online]. [Accessed: 16-Nov-2014]. [5] Jokowi, Sang Pemimpin Fenomenal, nasional.inilah.com. [Online]. [6] P. J. R. B. Tips and T. says, Profil Jokowi I Biodata Lengkap Joko Widodo Dunia Baca dot Com.. [7] Berita Dunia: Jokowi, Presiden Terpilih Pertama yang Tak Terkait Soeharto, beritasatu.com. [Online]. [8] Indonesia Baru yang Munafik (Jokowi-JK), KOMPASIANA.com. [Online]. [9] Kandunk, Jadi Penipu, Jokowi Belajar Sama Siapa Ya?, Silontong.com: Berita dan Ulasan Menarik.. [10] L. Muflikhah, SENTIMENT ANALYSIS PADA REVIEW BARANG BERBAHASA INDONESIA DENGAN METODE K-NEAREST NEIGHBOR (K-NN). [Online]. [Accessed: 03-Sep-2014]. [11] B. Pang and L. Lee, Movie Review Data, Movie Review Data. [Online]. [Accessed: 27-Dec-2014]. [12] J. Skinner, Searching databases tips to save you time when finding information, A guide to effective database searching, Sep [Online]. [Accessed: 06-Jan-2015]. [13] B. Pang and L. Lee, Opinion Mining and Sentiment Analysis, Found Trends Inf Retr, vol. 2, no. 1 2, pp , Jan [14] J. Blitzer, Domain adaptation for sentiment classification. [Online]. [Accessed: 1

2 03-Sep-2014]. [15] V. L. Sauter, Decision Support Systems for Business Intelligence. John Wiley & Sons, [16] S. Rahmawati, SELFIE: PERANAN JENIS KOMENTARTERHADAP HUBUNGAN ANTARA KECEMASAN SOSIAL DAN PERILAKU AGRESIF PELAKU SELFIE, psikologi.ub.ac.id. [Online]. content/uploads/2014/11/sartika- Rahmawati_ _Psikologi_Jurnal.pdf. [Accessed: 25-Nov- 2014]. [17] G. Agung, PERANCANGAN DAN IMPLEMENTASI SISTEM KLASIFIKASI KOMENTAR DENGAN ALGORITMA NAÏVE BAYES CLASIFIER, [Online]. al%20ta.docx. [Accessed: 25-Nov-2014]. [18] N. Adiyasa, Sentiment Analysis Menggunakan Pendekatan Lexicon- Based, Catatan Kecil. [Online]. [Accessed: 02-Dec-2014]. [19] sastrawi/sastrawi, GitHub. [Online]. [Accessed: 11-Nov-2014]. [20] F. Z. Tala, A Study of Stemming Effects on Information Retrieval in Bahasa Indonesia, [Online]. &q=a+study+of+stemming+effects+on+information+retrieval+in+bahasa+ Indonesia&type=&ts=&ref=&gws_rd=ssl. [Accessed: 29-Dec-2014]. [21] P. Palanisamy, Serendio: Simple and Practical lexicon based approach to Sentiment Analysis - Google Cendekia. [Online]. tical+lexicon+based+approach+to+sentiment+analysis&hl=id&as_sdt=0,5. [22] J. K. Wibisono and M. S. Drs. Edi Winarko, OPINION MINING PADA TWITTER UNTUK BAHASA INDONESIA DENGAN METODE SUPPORT VECTOR MACHINE DAN METODE BERBASIS LEXICON, Universitas Gadjah Mada, [23] Samsung, RIM Digugat karena Gunakan Emoticons, KOMPASIANA.com. [Online]. [24] J. Read, Using emoticons to reduce dependency in machine learning techniques for sentiment classification, Proceedings of the ACL Student Research Workshop. [Online]. [Accessed: 24-Feb- 2015]. [25] A. F. Hidayatullah and M. T. Dr. Azhari SN, ANALISIS SENTIMEN DAN KLASIFIKASI KATEGORI TERHADAP TOKOH PUBLIK PADA DATA TWITTER MENGGUNAKAN NAIVE BAYES CLASSIFIER, 2

3 Universitas Gadjah Mada, [26] V. K. Singh, R. Piryani, A. Uddin, P. Waila, and Marisha, Sentiment analysis of textual reviews; Evaluating machine learning, unsupervised and SentiWordNet approaches, in th International Conference on Knowledge and Smart Technology (KST), 2013, pp [27] Quadratic Programming MATLAB. [Online]. [Accessed: 07-Dec-2014]. [28] D. Kerami and H. Murfi, Kajian Kemampuan Generalisasi Support Vector Machine dalam Pengenalan Jenis Splice Sites Pada Barisan DNA, 03- Dec [Online]. [Accessed: 08-Mar-2015]. [29] G. Holmes, A. Donkin, and I. H. Witten, WEKA: a machine learning workbench, in Proceedings of the 1994 Second Australian and New Zealand Conference on Intelligent Information Systems,1994, 1994, pp [30] E. Frank, M. Hall, L. Trigg, G. Holmes, and I. H. Witten, Data mining in bioinformatics using Weka, Bioinformatics, vol. 20, no. 15, pp , Oct [31] metode naive bayes sentiment analysis - Google Cendekia. [Online]. s&btng=&hl=id&as_sdt=0%2c5. [Accessed: 17-Nov-2014]. [32] M. Merina, Klasifikasi Dokumen Beropini Me nggunakan Metode Naive Bayes dan Metode Categorical Pr oportional Difference, Klasifikasi Dok. Beropini Me Nggunakan Metode Naive Bayes Dan Metode Categ. Pr Oportional Differ., [33] metode knn sentiment analysis - Google Cendekia. [Online]. =&hl=id&as_sdt=0%2c5. [Accessed: 17-Nov-2014]. [34] metode multinomial naive bayes sentiment analysis - Google Cendekia. [Online]. iment+analysis&btng=&hl=id&as_sdt=0%2c5. [Accessed: 17-Nov-2014]. [35] V. Narayanan, I. Arora, and A. Bhatia, Fast and Accurate Sentiment Classification Using an Enhanced Naive Bayes Model, in Intelligent Data Engineering and Automated Learning IDEAL 2013, H. Yin, K. Tang, Y. Gao, F. Klawonn, M. Lee, T. Weise, B. Li, and X. Yao, Eds. Springer Berlin Heidelberg, 2013, pp [36] W. Zheng and Q. Ye, Sentiment Classification of Chinese Traveler Reviews by Support Vector Machine Algorithm, in Third International Symposium on Intelligent Information Technology Application, IITA 2009, 2009, vol. 3, pp [37] A. Shoukry and A. Rafea, Sentence-level Arabic sentiment analysis, in 2012 International Conference on Collaboration Technologies and Systems (CTS), 2012, pp

4 [38] A. Balahur and M. Turchi, Comparative Experiments for Multilingual Sentiment Analysis Using Machine Translation. [Online]. ceur-ws.org/vol-917/sdad2012_8_balahur.pdf. [Accessed: 07- Dec-2014]. [39] M. Choy, M. L. F. Cheong, M. N. Laik, and K. P. Shung, A sentiment analysis of Singapore Presidential Election 2011 using Twitter data with census correction, ArXiv Cs Stat, Aug [40] A. Ceron, L. Curini, S. M. Iacus, and G. Porro, Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens political preferences with an application to Italy and France, New Media Soc., p , Apr [41] S. Rill, D. Reinel, J. Scheidt, and R. V. Zicari, PoliTwi: Early detection of emerging political topics on twitter and the impact on conceptlevel sentiment analysis, Knowl.-Based Syst., vol. 69, pp , Oct [42] D. J. Hopkins and G. King, A Method of Automated Nonparametric Content Analysis for Social Science, Am. J. Polit. Sci., vol. 54, no. 1, pp , Jan [43] NoSQL Database Model untuk Social Network dan web 2.0. [Online]. Network_dan_web_2.0. [Accessed: 06-Jan-2015]. [44] University of Reading. [Online]. [Accessed: 06-Jan- 2015]. [45] C. R. Hildreth, The use and understanding of keyword searching in a university online catalog, Inf. Technol. Libr., vol. 16, no. 2, pp , [46] P. Ensor, User Practices in Keyword and Boolean Searching on an Online Public Access Catalog, Inf. Technol. Libr., vol. 11, no. 3, pp , Jan [47] P. Ensor, Knowledge Level of Users and Nonusers of Keyword/Boolean Searching on an Online Public Access Catalog, RQ, vol. 32, no. 1, pp , Oct [48] R. A. Sit, Online library catalog search performance by older adult users, Libr. Inf. Sci. Res., vol. 20, no. 2, pp , [49] Nigel Ford, David Miller, and Nicola Moss, Web search strategies and retrieval effectiveness: an empirical study, J. Doc., vol. 58, no. 1, pp , Feb [50] U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth, From Data Mining to Knowledge Discovery in Databases, AI Mag., vol. 17, no. 3, p. 37, Mar [51] ARTIKEL ILMIAH ALGORITMA SUPPORT VECTOR MACHINE UNTUK MEMPREDIKSI RENTET WAKTU HARGA DAGING AYAM BROILER DAN TELUR AYAM BROILER PROGRAM PASCA SARJANA MAGISTER TEKNIK INFORMATIKA UNIVERSITAS DIAN NUSWANTORO SEMARANG [Online]. 4

5 PPORT_VECTOR_MACHINE_UNTUK_MEMPREDIKSI_RENTET_WAK TU_HARGA_DAGING_AYAM_BROILER_DAN_TELUR_AYAM_BROIL ER_PROGRAM_PASCA_SARJANA_MAGISTER_TEKNIK_INFORMATI KA_UNIVERSITAS_DIAN_NUSWANTORO_SEMARANG_2014. [Accessed: 27-Nov-2014]. [52] V. Moertini, Data Mining Sebagai Solusi Bisnis, Data Mining Sebagai Solusi Bisnis. [Online]. le%20pdf/idatamining_ok.pdf. [Accessed: 02-Dec-2014]. [53] N. M. Huda, Aplikasi Data Mining Untuk Menampilkan Informasi Tingkat Kelulusan Mahasiswa (Studi Kasus di Fakultas MIPA Universitas Diponegoro), other, FACULTY OF MATHEMATICS AND NATURAL SCIENCES, [54] N. S. YUDA, Data Mining Menggunakan Algoritma Naïve Bayes Untuk Klasifikasi Kelulusan Mahasiswa Universitas Dian Nuswantoro. ( Studi Kasus: Fakultas Ilmu Komputer Angkatan 2009 )., SkripsiFakultas Ilmu Komput., [55] B. Warsito, D. Ispriyanti, and H. Widayanti, CLUSTERING DATA PENCEMARAN UDARA SEKTOR INDUSTRI DI JAWA TENGAH DENGAN KOHONEN NEURAL NETWORK, J. PRESIPITASI, vol. 4, no. 1, pp. 1 6, Mar [56] N. D. Putranti and E. Winarko, Analisis Sentimen Twitter untuk Teks Berbahasa Indonesia dengan Maximum Entropy dan Support Vector Machine, IJCCS - Indones. J. Comput. Cybern. Syst., vol. 8, no. 1, pp , Jan [57] K. Denecke, Using SentiWordNet for multilingual sentiment analysis, pp , [58] Thumbs Up Sentiment Classification using Machine Learning Techniques - Sentiment Analysis. [Online]. ificationusingmachinelearningtechniques. [Accessed: 04-Oct-2014]. [59] H. Eldira, E. M. K, and N. R. MUBTADAI, WEB MINING UNTUK PENCARIAN DOKUMEN BAHASA INGGRIS MENGGUNAKAN HILL CLIMBING AUTOMATIC CLUSTERING, EEPIS Final Proj., [60] sastrawi/sastrawi, GitHub. [Online]. [Accessed: 03-Dec-2014]. [61] sastrawi/sastrawi, GitHub. [Online]. [Accessed: 03-Dec-2014]. [62] ivanlanin/kateglo, GitHub. [Online]. [Accessed: 03-Dec-2014]. [63] B. Nazief and M. Adriani, Algoritma Nazief dan Adriani. [Online]. agusdwi89.web.ugm.ac.id/ir/stemming.pdf. [Accessed: 03-Dec- 2014]. [64] H. Februariyanti, E. Zuliarso, and M. S. Utomo, PROTOTIPE MESIN PENCARI DOKUMEN TEKS, 18-Aug [Online]. [Accessed: 03-Dec-2014]. 5

6 [65] N. Kurniawan, IMPLEMENTASI D AN ANALISIS STEMMING MENGGUNAKAN N-GRAM DALAM SISTEM INFORMATION RETRIEVAL, telkomuniversity.ac.id. [Online]. 04_752db621a8686c3a5dd1af327f0d862f.pdf. [Accessed: 03-Dec-2014]. [66] T. Putra, Klasifikasi Severity Dari Bug Untuk Proyek Perangkat Lunak, narotama.ac.id. [Online]. SEVERITY%20DARI%20BUG%20UNTUK%20PROYEK%20PERANGKA T%20LUNAK.pdf. [Accessed: 03-Dec-2014]. [67] P. Pandu, Kamus Kata Dasar dan Stopword List Bahasa Indonesia, Kamus Kata Dasar dan Stopword List Bahasa Indonesia. [Online]. [Accessed: 03-Dec-2014]. [68] A. Aggarwal, A. Rajadesingan, and P. Kumaraguru, PhishAri: Automatic realtime phishing detection on twitter, in ecrime Researchers Summit (ecrime), 2012, 2012, pp [69] Twitter, Mashable. [Online]. [Accessed: 29-Nov-2014]. [70] S. G. Mazman and Y. K. Usluel, Modeling educational usage of Facebook, Comput. Educ., vol. 55, no. 2, pp , Sep [71] M. Zhou, L. Lei, J. Wang, W. Fan, and A. G. Wang, Social Media Adoption and Corporate Disclosure, J. Inf. Syst., Oct [72] K. Wallsten, Beyond Agenda Setting: The Role of Political Blogs as Sources in Newspaper Coverage of Government, in th Hawaii International Conference on System Sciences (HICSS), 2011, pp [73] I. Purba, Metode Holistic Lexicon-Based untuk Analisis Sentimen pada Dokumen Bahasa Indonesia (Studi Kasus: Tweets mengenai Isu Sosial Kota Bandung), cdndata.telkomuniversity.ac.id. [Online]. 32_6183cc0a752d0be16e529dbe95209f40.pdf. [Accessed: 01-Dec-2014]. [74] E. H. Kristanto, USING KAKAO TALK S EMOTICON FLASH CARDS TO IMPROVE THE SPEAKING SKILL OF THE ELEVENTH GRADERS OF SMAN 4 BLITAR, SKRIPSI Jur. Sastra Ingg. - Fak. Sastra UM, vol. 2014, no. 2014, Oct [75] M. Boia, B. Faltings, C.-C. Musat, and P. Pu, A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets, in 2013 International Conference on Social Computing (SocialCom), 2013, pp [76] M. Choy, M. L. F. Cheong, M. N. Laik, and K. P. Shung, A sentiment analysis of Singapore Presidential Election 2011 using Twitter data with census correction, ArXiv Cs Stat, Aug [77] Tentang Jokowi Jokowi Center.. [78] Y. Thayrun, Jokowi: Pemimpin Rakyat Berjiwa Rocker. NouraBooks, [79] Y. P. M. A. (YAPAMA), Tabloid Reformata Edisi 175 Mei

7 Yayasan Pelayanan Media Antiokhia (YAPAMA), [80] C. Darujati, Pemanfaatan Teknik Supervised untuk Klasifikasi Teks Bahasa Indonesia, narotama.ac.id. [Online]. Link%20Vol%2016%20February% pdf. [Accessed: 03-Dec-2014]. [81] A. Nurani, Implementasi naïve bayes classifier pada program bantu penentuan buku referensi matakuliah, ukdw.ac.id. [Online]. [Accessed: 03-Dec-2014]. [82] J. Platt, Sequential minimal optimization: A fast algorithm for training support vector machines, msr-waypoint.com. [Online]. [Accessed: 04-Dec- 2014]. [83] E. Purwanto, Perbandingan Strategi Replikasi Pada sistem basis data terdistribusi, binadarma.ac.id. [Online]. TEGI%20REPLIKASI%20PADA%20SISTEM%20BASIS%20DATA%20TE RDISTRIBUSI.pdf. [Accessed: 06-Dec-2014]. [84] B. Santosa, Tutorial Support Vector Machine, Ambil Berkas. [Online]. oc.its.ac.id/ambilfile.php?idp=1223. [Accessed: 03-Feb- 2015]. [85] A. M. Zamani, B. Amaliah, and A. Munif, Implementasi Algoritma Genetika pada Struktur Backpropagation Neural Network untuk Klasifikasi Kanker Payudara, J. Tek. ITS, vol. 1, no. 1, pp. A222 A227, Sep