DAFTAR PUSTAKA [1] Bernadin, D. N., & Tulasi, D. (2015). Adwords Terhadap Perilaku Share Pengunjung Situs Wego Indonesia. Universitas Bina Nusantara – Jurnal. 1–11. [2] Wallace, T. (n.d.). Create Facebook Ad Campaigns. [Online] Retrieved August 15, 2017, from https://www.bigcommerce.com/blog/create-facebook-ad-campaigns/ [3] Krushevskaja, D., & Simpson, W. (2016). Ad Allocation with Secondary Metrics, 1202-1211. 2016 IEEE International Conference on Big Data (Big Data) Ad. [4] Fuchs, C. (2012). With or Without Marx ? With or Without Capitalism ? A Re- joinder to Adam Arvidsson and Eleanor Colleoni ., 10(2), 633–645. [5] Patel, N. (n.d.). The 5 Important Metrics of Facebook Ad Campaign. [Online] Retrieved April 10, 2017, from Neil Patel: http://neilpatel.com/blog/the-5-important-metrics-of-facebook-adcampaigns/ [6] Nabi-Abdolyousefi, R. (2014). Conversion Rate Prediction in Search Engine Marketing. Grad. School of Natural and Applied Sci. - Thesis & Dissertations. Istanbul. [7] Palupi, H. (2016, May). Kuasai Informasi dengan Big Data dan Machine Learning Codefest Kudo.
[Online]
Retrieved
April
10,
2017,
from
Codepolitan:
https://www.codepolitan.com/kuasai-informasi-dengan-big-data-dan-machine-learningcodefest-kudo [8] Hoachuck, J., Singh, S., & Yamada, L. (2016). Outbrain Click Prediction. CS229 Machine Learning Autumn 2016 Project Paper. Stanford University. [9] Ray, S. (2015). Build Predictive Model 10 Minutes Python. [Online] Retrieved April 5, 2017, from Analytics Vidya: https://www.analyticsvidhya.com/blog/2015/09/build-predictivemodel-10-minutes-python/ [10] Dembczynski, K., Kotlowski, W., & Weiss, D. (2008). Predicting Ads’ Click-Through Rate with Decision Rules. Workshop on Targeting and Ranking in Online Advertising, WWW ’0. In:
TROA
2008,
Beijing,
China.
Retrieved
from
http://www.cs.put.poznan.pl/dweiss/research/adrules/papers/troa.pdf [11] Chaudhari, P., Dingankar, R., & Chaudhari, R. (2013). Prediction of CPC using Neural Networks for Minimization of Cost. International Journal of Computer Theory and
Engineering, 5(4), 650-. https://doi.org/10.7763/IJCTE.2013.V5.768. [12] He, X., Bowers, S., Candela, J. Q., Pan, J., Jin, O., Xu, T., … Herbrich, R. (2014). Practical Lessons from Predicting Clicks on Ads at Facebook. Proceedings of 20th ACM SIGKDD Conference
on
Knowledge
Discovery
and
Data
Mining
-
ADKDD’14,
1–9.
https://doi.org/10.1145/2648584.2648589. [13] Facebook Business. (n.d.). Retrieved May 8, 2017, from Prepare to Advertise on Facebook: https://www.facebook.com/business/help/714656935225188/?helpref=hc_fnav [14] Advertising Objectives. (n.d.). [Online] Retrieved May 8, 2017, from Facebook Business: https://www.facebook.com/business/help/197976123664242/?helpref=hc_fnav [15] Helft, M. (2007). Google tests an ad idea: Pay only for results. The New York Times, March 21. [16] Afif Riyadi, A. (2017). Tech in Asia City Chapters Meetup (Jakarta): “Paid Advertising & Maximizing ROI.” Retrieved July 6, 2017, from https://id.techinasia.com/talk/tia-citychapters-meetup-jakarta [17] Santosa, B. (2007). Data Mining: Teknik Pemanfaatan Data untuk Keperluan Bisnis. Graha Ilmu. Yogyakarta. [18] Larose, D.T. (2005). Discovering Knowledge in Data: An Introduction to Data Mining. John Willey & Sons, Inc. [19] Dicky Nofriansyah, S.Kom., M. K. (2015). Buku: Konsep Data Mining Vs Sistem Pendukung Keputusan.
Medan:
Deepublish.
Retrieved
from
https://books.google.co.id/books/about/Konsep_Data_Mining_Vs_Sistem_Pendukung_K.ht ml?id=PoJyCAAAQBAJ&redir_esc=y [20] Janitza, A. B. S. (2012). Overview of Random Forest Methodology and Practical Guidance with Emphasis on Computational Biology and Overview of Random Forest Methodology and Practical Guidance with Emphasis on Computational Biology and Bioinformatics. Technical Report Number 129, 2012 Department of Statistics University of Munich. [21] Liaw, A., & Wiener, M. (2002). Classification and Regression by randomForest, 2(December), 18–22. [22] Cutler, A (2013) Trees and random forests. NIH 1R15AG037392-01, p 92. Cutler. http://www.math.usu.edu/adele/RandomForests/ UofU2013.pdf.
[23] Dwi, L., Pratiwi, B., Wibowo, W., & Statistika, J. (2015). Klasifikasi Nilai Peminat SBMPTN ( Seleksi Bersama Masuk Perguruan Tinggi Negeri ) ITS dengan Pendekatan Classification and Regression Trees ( CART ), 4(2), 2–7. Jurnal Sains Dan Seni ITS Vol. 4, No.2, (2015) 2337-3520. [24] Dhawangkhara, M. (2017). Prediksi Intensitas Hujan Kota Surabaya Dengan Matlab Menggunakan Teknik Random Forest Dan Cart (Studi Kasus Kota Surabaya). Surabaya. Jurnal Teknik ITS Vol. 6, No. 1, (2017) ISSN: 2337-3539. [25] Sartono, B., & Syafitri, U. D. (2010). Metode Pohon Gabungan : Solusi Pilihan Untuk Mengatasi Kelemahan Pohon Regresi Dan Klasifikasi Tunggal ( Ensemble Tree : An Alternative toward Simple Classification and Regression Tree ). Vol 15 No.1. Forum Statistika dan Komputasi, April 2010 p : 1-7 ISSN : 0853-8115 [26] E. C. P. a. F. B. S. B. B. A. Goldstein. (2011). Random forests for genetic association studies. Statistical Applications in Genetics and Molecular Biology. [27] F. J. O. R. S. C. Breiman L. (1984). Classification and Regression Trees, New York: Chapman & Hall.S [28] L. C. Thomas. (2000). A survey of credit and behavioural scoring: Forecasting financial risk of lending to consumers. International Journal of Forecasting, vol. 16(2). [29] H. James Wilson, N. M. (n.d.). Sales Gets a Machine-Learning Makeover. [Online] Retrieved June 20, 2017, from MIT Sloan: http://sloanreview.mit.edu/article/sales-gets-a-machinelearning-makeover/ [30] Breiman L. (2004). Consistency for a simple model of random forests. In Technical Report 670 Technical report, Department of Statistics, University of California, Berkeley, USA. [31] Breiman, L. E. O. (2001). Random Forests, 5–32. Machine Learning Journal, 45, 5–32. Department of Statistics, University of California, Berkeley, USA. [32] Dhawangkhara, M. (2017). Prediksi Intensitas Hujan Kota Surabaya dengan MatLab menggunakan Teknik Random Forest dan CART (Studi Kasus Kota Surabaya), 6(1), 149. Retrieved from http://repository.its.ac.id/1657/ [33] W. S. J. Saputra, A. R. Sujatmika, dan A. Z. Arifin, “Seleksi Fitur Menggunakan Random Forest Dan Neural Network,” 13th Ind. Electron. Semin. 2011 (IES 2011) Electron. Eng. Polytech. Inst. Surabaya (EEPIS)., pp. 978–979, 2011.
[34] Eka, F., & Zain, I. (2014). Klasifikasi Pengangguran Terbuka Menggunakan CART ( Classification and Regression Tree ) di Provinsi Sulawesi Utara. Jurnal Sains Dan Seni Pomits, 3(1), 2337–3520. [35] Hu, Y. (Jeffrey), Shin, J., & Tang, Z. (2016). Incentive Problems in Performance-Based Online Advertising Pricing: Cost per Click vs. Cost per Action. Management Science Journal, 2022–2038. Vol. 62, No. 7, July 2016, pp. 2022–2038 ISSN 0025-1909 (print). https://doi.org/10.1287/mnsc.2015.2223. [36] Zhang, Y., & Haghani, A. (2015). A gradient boosting method to improve travel time prediction A gradient boosting method to improve travel time prediction. Transportation Research Part C, (March). Department of Civil & Environmental Engineering, University of Maryland,
College
Park,
MD
20740,
United
States
article.
https://doi.org/10.1016/j.trc.2015.02.019. [37] Miralles, L. (2015). Online Advertising and the CPA Model : Challenges and Opportunities. International Journal of Engineering and Management Research 4 (3), 324-334. [38] Machado, G., Recamonde-mendoza, M., Machado, G., Mendoza, M. R., & Corbellini, L. G. (2015). What variables are important in predicting bovine viral diarrhea virus ? A random forest approach. Veterinary Research, (July). https://doi.org/10.1186/s13567-015-0219-7. [39] Do Splitting Rules Really Matter? (n.d.). [Online] Retrieved July 15, 2017, from https://www.salford-systems.com/resources/whitepapers/do-splitting-rules-really-matter [40] Alabdulkarim, A. (2017). Measuring The Impact of Social Media Marketing on Individuals Measuring The Impact of Social Media Marketing on Individuals. Student Theses, Papers and Projects (Computer Science), Western Oregon University. [41] Facebook. (n.d.). Glossary of Ad Terms. [Online] Retrieved July 19, 2017, from https://www.facebook.com/business/help/447834205249495 [42] Chapelle, O. (n.d.). Simple and scalable response prediction for display advertising. ACM Trans.
Intell.
Syst.
Technol.
V,
N,
Article
A,
V(212),
1–34.
https://doi.org/10.1145/0000000.0000000. [43] Florkowski, C. M. (2008). Sensitivity, Specificity, Receiver-Operating Characteristic (ROC) Curves and Likelihood Ratios: Communicating the Performance of Diagnostic Tests. The Clinical Biochemist Reviews, 29(Suppl 1), S83–S87.
[44] Wallace, T. (n.d.). Create Facebook Ad Campaigns. [Online] Retrieved August 15, 2017, from https://www.bigcommerce.com/blog/create-facebook-ad-campaigns/ [45] Jin, C., De-Lin, L., & Fen-Xiang, M. (2009, July). An improved ID3 decision tree algorithm. In Computer Science & Education, 2009. ICCSE'09. 4th International Conference on (pp. 127-130). IEEE. [46] Nurina Sari, B. (2016). Implementasi Teknik Seleksi Fitur Information Gain Pada Algoritma Klasifikasi Machine Learning Untuk Prediksi Performa Akademik Siswa. Seminar Nasional Teknologi Informasi Dan Multimedia 2016, (February), 6. Retrieved from http://semnas.amikom.ac.id/document/pdf/1482.pdf [47] M. Ramaswami, R. Bhaskaran, “A Study on Feature Selection Techniques in Educational Data Mining”, Journal Of Computing, vol. 1, Issue 1, pp. 7-11. December 2009. [48] Niswatin, R. K., & Wulanningrum, R. (2017). Penerapan Algoritma Decision Tree Pada Penentuan Keberhasilan Akademik Mahasiswa, 2–7. Seminar Nasional Teknologi Informasi dan Multimedia 2017, STMIK AMIKOM Yogyakarta, ISSN : 2302-3805. [49] Slamet, A. (2008). Buku: Manajemen Sumber Daya Manusia. Unnes Press, ISBN: 979 100 644 x. Universitas Negeri Semarang, Semarang.
[50] Harryanto, F. F., & Hansun, S. (2017). Penerapan Algoritma C4 . 5 untuk Memprediksi Penerimaan Calon Pegawai Baru di PT WISE. Jatisi, 3(2), 95–103. [51] Tjahyono, A. dan Anggara, A. M., 2010, Sistem Pendukung Keputusan Penerimaan Pegawai Baru pada PT. Kanasritex Semarang. IJCCS, Vol. 9 No.3. [52] C4.5 Algorithm. (n.d.). [Online] Retrieved from https://en.wikipedia.org/wiki/C4.5_algorithm [53] Mohiuddin, M. (2016). Decision Tree - Random Forest Code. [Online] Retrieved from https://github.com/maksoodmohiuddin/decision_tree/blob/master/decision_tree.py