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47 BIBLIOGRAPHY Akvo , 2015 , Vanuatu HH Size and Water Point Functionality Visualization , http://akvo.cartodb.com/viz/b77c914a-cdc8-11e4-b131- 0e4fddd5de28/embed_map [Accessed March 10, 2015]w Batool, R., Khattak, A.M., Maqbool, J., & Lee, S., 2013. Precise Tweet Classification and Sentiment Analysis. Computer and Information Science (ICIS), 20133 IEEE/ACIS 12th Conference, pp.451-466. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumbe r=6607883 [Accessed March 10, 2015]. Bhuta, S., Doshi, A., Doshi, U., & Narvekar, M., 2014. A Review of Techniques for Sentiment Analysis of Twitter Data. Issues and Challenges in Intelligent Computing Techniques (ICICIT), 2014 International Conference, pp.583- 591. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumbe r=6781346 [Accessed March 10, 2015]. Boutet, A., Hyoungshick Kim, & Yoneki, E., 2012. What’s in Twitter: I Know What Parties are Popular and Who You are Supporting Now!. Advances in Social Network Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference, pp.132-139. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumbe r=6425772 [Accessed March 10, 2015]. Bradley T, 2015. The Unplumbed Depths of Government Data. Available at http://motherboard.vice.com/read/the-unplumbed-depths-of-government- data [Accessed March 10, 2015]. CartoDB, 2015, Tweet From Local and Tourist , https://satyanugraha1.cartodb.com/maps [Accessed March 10, 2015] Chen, X., Vorvoreanu, M., & Madhavan, K.P.C., 2014. Mining Social Media Data for Understanding Student’s Learning Experiences. IEEE Transactions on Learning Technologies, Vol. 7, No.3. Available at: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6406574 [Accessed March 10, 2015]. Cheng, Z., Caverlee, J., & Lee, K., 2010. You Are Where You Tweet: A Content- Based Approach to Geo-locating Twitter Users. Proceeding CIKM ’10 Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 759-768. Available at http://infolab.cse.tamu.edu/static/papers/cikm1184c-cheng.pdf [Accessed March 10, 2015]. Cho, S. H., & Kang, H. B., 2012. Statistical Text Analysis and Sentiment Classification in Social Media. Systems, Man, and Cybernetics (SMC), CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USER HISTORICAL DATA SATYA NUGRAHA, Edi Winarko, M.Sc., Ph.D Universitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/

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BIBLIOGRAPHY

Akvo , 2015 , Vanuatu HH Size and Water Point Functionality Visualization , http://akvo.cartodb.com/viz/b77c914a-cdc8-11e4-b131-0e4fddd5de28/embed_map [Accessed March 10, 2015]w

Batool, R., Khattak, A.M., Maqbool, J., & Lee, S., 2013. Precise Tweet Classification and Sentiment Analysis. Computer and Information Science (ICIS), 20133 IEEE/ACIS 12th Conference, pp.451-466. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6607883 [Accessed March 10, 2015].

Bhuta, S., Doshi, A., Doshi, U., & Narvekar, M., 2014. A Review of Techniques for Sentiment Analysis of Twitter Data. Issues and Challenges in Intelligent Computing Techniques (ICICIT), 2014 International Conference, pp.583-591. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6781346 [Accessed March 10, 2015].

Boutet, A., Hyoungshick Kim, & Yoneki, E., 2012. What’s in Twitter: I Know What Parties are Popular and Who You are Supporting Now!. Advances in Social Network Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference, pp.132-139. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6425772 [Accessed March 10, 2015].

Bradley T, 2015. The Unplumbed Depths of Government Data. Available at http://motherboard.vice.com/read/the-unplumbed-depths-of-government-data [Accessed March 10, 2015].

CartoDB, 2015, Tweet From Local and Tourist , https://satyanugraha1.cartodb.com/maps [Accessed March 10, 2015]

Chen, X., Vorvoreanu, M., & Madhavan, K.P.C., 2014. Mining Social Media Data for Understanding Student’s Learning Experiences. IEEE Transactions on Learning Technologies, Vol. 7, No.3. Available at: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6406574 [Accessed March 10, 2015].

Cheng, Z., Caverlee, J., & Lee, K., 2010. You Are Where You Tweet: A Content-Based Approach to Geo-locating Twitter Users. Proceeding CIKM ’10 Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 759-768. Available at http://infolab.cse.tamu.edu/static/papers/cikm1184c-cheng.pdf [Accessed March 10, 2015].

Cho, S. H., & Kang, H. B., 2012. Statistical Text Analysis and Sentiment Classification in Social Media. Systems, Man, and Cybernetics (SMC),

CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USERHISTORICAL DATASATYA NUGRAHA, Edi Winarko, M.Sc., Ph.DUniversitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/

48

48

IEEE International Conference, pp.1112-1117. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6377880 [Accessed March 10, 2015].

Cox, M., & Ellsworth, D., 1997. Application-Controlled Demand Paging for Out-of-Core Cisualization. Report NAS-97-010, July 1997, pp.1-11. Acaailable at https://www.nas.nasa.gov/assets/pdf/techreports/1997/nas-97-010.pdf [Accessed March 10, 2015].

Datacanvas, 2015, Sensor Data, http://datacanvas.org [Accessed March 10, 2015] Gauvin, W., Chen, C., Xinwen Fu & Benyuan Liu, 2011. Classification of

Commercial and Personal Profiles on MySpace. Pervasive Computing and Communications Workshops (PERCOM Workshops), 2011 IEEE International Conference, pp.276-281. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=5766883 [Accessed March 10, 2015].

Hao, M., Rohrdantz, C., Janetzko, H., & Dayal, U., 2011. Visual Sentiment Analysis on Twitter Data Streams. Visual Analytics Science and Technologu (VAST), 2011 IEEE Conference, pp.277-278. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6102472 [Accessed March 10, 2015].

Kerber M., 2004, Artificial Intelligence Decision Tree, http://www.cs.bham.ac.uk/~mmk/Teaching/AI/figures/dectree-orig.jpg [Sccessed March 15, 2015]

Laksana, J., & Purwarianti, A., 2014. Indonesian Twitter Text Authority Classification For Government in Bandung. Advanced InformaticsL Concept, Theory and Application (ICAICTA), pp.129-134. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=7005928 [Accessed March 10, 2015].

Leetaru K, 2014. Big Data Big Potential. Available at http://www.cfr.org/digital-infrastructure/big-data-big-potential/p33682 [Accessed March 10, 2015].

Liu, H., Luo, B., & Dongwon, L., 2012. Location Type Classification Using Tweet Content. Machine Learning and Applications (ICMLA), pp.232–237. Available at: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6406574 [Accessed March 10, 2015].

Lunando, E., & Purwarianti, A., 2013. Indonesian Social Media Sentiment Analysis with Sarcasm Detection. Advanced Computer Science and Information Systems (ICACSIS), 2013 International Conference, pp.195-198. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6761575 [Accessed March 10, 2015].

McCormick, 2013, K-Fold Cross Validation, https://chrisjmccormick.files.wordpress.com/2013/07/10_fold_cv.png

CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USERHISTORICAL DATASATYA NUGRAHA, Edi Winarko, M.Sc., Ph.DUniversitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/

49

49

[Accessed May 15, 2015]

Naradhipa, A. R., & Purwarianti, A., 2011. Sentiment Classification for Indonesian Message in Social Media. Electrical Engineering and Informatics (ICEEI), pp.1-4. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6021696 [Accessed March 10, 2015].

Neethu, M.S., & Rajasree, R., 2013. Sentiment Analysis in Twitter using Machines Learning Techniques. Computing, Communication and Networking Technologies (ICCCNT), 2013 Fourth International Conference, pp.1-5. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6726818 [Accessed March 10, 2015].

Nithya, K., Kalaivaani, P.C.D., & Thangarajan, R., 2012. An Enhanced Data Mining Model for Text Classification. Computing, Communication and Application (ICCCA), 2012 International Conference, pp.1-4. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6179179 [Accessed March 10, 2015].

Pewtrust, 2015, Moving Cities Beyond Performance Measurement, http://www.pewtrusts.org/en/research-and-analysis/analysis/2015/02/04/moving-cities-beyond-performance-measurement [Accessed March 10, 2015]

Raharjo, S., & Winarko, E., 2014. Klasterisasi, Klasifikasi dan Peringkasan Teks Berbahasa Indonesia. Prosiding Seminar Ilmiah Nasional Komputer dan Sistem Intelijen (KOMMIT 2014), pp.391-401. Available at http://repository.akprind.ac.id/sites/files/1004-2828-1-PB.pdf

Scipy, 2015, Python Scientific Lecture Notes, http://scipy-lectures.github.io/_images/svm_margin.png

Twitter, 2015, Adding Your Location, https://support.twitter.com/articles/122236-adding-your-location-to-a-tweet [Accessed March 10,2015]]

Vongsingthong, S., & Wisitpongphan, N., 2014. Classification of University Students’ Behaviors in Sharing Information on Facebook. Computer Science and Software Engineering (JCSSE), 2014 11th International Joint Conference, pp.134-139. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6841856 [Accessed March 10, 2015].

Wijaya, V., Erwin, A., Galinium, M., & Muliady, W., 2013. Automatic Mood Classification of Indonesian Tweets Using Linguistic Approach. Information Technology and Electrical Engineering (ICITEE), 2013 International Conference, pp.41-46. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6676208 [Accessed March 10, 2015].

Witten, I. H., Frank, E., and Hall, M. A., 2011, Data Mining Practical Machine

CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USERHISTORICAL DATASATYA NUGRAHA, Edi Winarko, M.Sc., Ph.DUniversitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/

50

50

Learning Tools and Techniques, 3rd Edition, Morgan Kaufmann, Burlington.

Zhang, L., Li, Y., Sun, C., & Nadee, W., 2013. Rough Set Based Approach to Text Classification. Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013 IEEE?WIC?ACM International Joint Conferences, pp.245-252. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6690735 [Accessed March 10, 2015].

CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USERHISTORICAL DATASATYA NUGRAHA, Edi Winarko, M.Sc., Ph.DUniversitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/