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DAFTAR PUSTAKA
Aggarwal, C. C. (2015). Data Mining: The Textbook. New York: Springer.
Aggarwal, C. C., & Yu, P. S. (2008). Privacy-Preserving Data Mining Models and Algorithms. New York: Springer.
Annie, L. C., & Kumar, A. (2012). Market Basket Analysis for a Supermarket based on Frequent Itemset Mining. International Journal of Computer Science.
Berndtsson, M., Hansson, J., Olsson, B., & Lundell, B. (2008). Thesis Projects A Guide for Students in Computer Science and Information Systems Second Edition. London: Springer.
Berry, M. J., & Linoff, G. S. (2004). Data Mining Techniques For Marketing, Sales, and Customer Relationship Management Second Edition. Canada:
Wiley.
Bhandari, A., Gupta, A., & Das, D. (2015). Improvised apriori algorithm using frequent pattern tree for real time applications in data mining. Procedia Computer Science (hal. 644-651). Elsevier.
Cavique, L. (2007). A scalable algorithm for the market basket analysis. Journal of Retailing and Consumer Services, 400-407.
Chandra, B., & Bhaskar, S. (2011). A new approach for generating efficient sample from market basket data. Expert Systems with Applications, 1321- 1325.
Chu, W. W. (2014). Data Mining and Knowledge Discovery for Big Data. Los Angeles: Springer.
Gorunescu, F. (2011). Data Mining Concepts, Models and Techniques. Berlin:
Springer.
Han, J., Kamber, M., & Pei, J. (2012). Data Mining Concept and Techniques Third Edition. Elsevier.
Hand, Mannila, & Smyth. (2001). Principles of Data Mining: Adaptive Computation and Machine Learning. Cambridge: MIT Press.
Harrington, P. (2012). Machine Learning in Action. Shelter Island: Manning.
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Hofmann, M., & Klinkenberg, R. (2014). Rapid Miner Data Mining Use Cases and Business Analytics Applications. CRC Press.
Jea, K.-F., Chang, M.-Y., & Lin, K.-C. (2004). An efficient and flexible algorithm for online mining of large itemsets. Information Processing Letters 92, 311–316.
Jiawei, H., & Kamber, M. (2006). Data Mining:Concepts and Techniques. USA:
Morgan Kaufmann.
Kothari. (2004). Research Methodology Methods and Techniques Second Revised Edition. New Delhi: New Age International (P) Limited.
Larose, D. T. (2005). Data Mining Methods and Models. Canada: Wiley- Interscience.
Li, Y., Ning, P., Wang, X. S., & Jajodia, S. (2003). Discovering calendar-based temporal association rules. Data & Knowledge Engineering, 193-218.
Maione, C., Paula, E. S., Gallimberti, M., Batista, B. L., Campiglia, A. D., Barbosa, F., & Barbosa, R. M. (2016). Comparative study of data mining techniques for the authentication of organic grape juice based on ICP-MS analysis. Expert Systems With Applications, 60-73.
Narvekar, M., & Syed, S. F. (2015). An optimized algorithm for association rule mining using FP tree. Procedia Computer Science (hal. 101-110).
Elsevier.
Prasad, P., & Malik, L. (2011). Using Association Rule Mining for Extracting Product Sales Patterns in Retail Store Transaction. International Journal on Computer Science and Engineering.
Prasetyo, E. (2014). Data Mining-Mengolah Data Menjadi Informasi Menggunakan Matlab. Yogyakarta: Andi.
Santosa, B. (2007). Data Mining:Teknik Pemanfaatan Data untuk Keperluan Bisnis. Yogyakarta: Graha Ilmu.
Song, M., & Rajasekaran, S. (2006). A Transaction Mapping Algorithm for Frequent Itemsets Mining. IEEE Transactions On Knowledge And Data Engineering, 472–481.
Venkatachari, K. (2016). Market Basket Analysis: Understanding Indian Consumer Buying Behavior Of Spain Market. BVIMSR’s Journal of Management Research.
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Videla-Cavieres, I. F., & Ríos, S. A. (2014). Extending market basket analysis with graph mining techniques: A real case. Expert Systems with Applications 41, 1928-1936.
Vu, L., & Alaghband, G. (2014). Novel parallel method for association rule mining on multi-core shared memory systems. Parallel Computing, 768- 785.
Wisaeng, K. (2014). Association Rule with Frequent Pattern Growth Algorithm for Frequent Item Sets Mining. Applied Mathematical Sciences, 4877- 4885.
Wu, F., Chiang, S.-W., & Lin, J.-R. (2007). A new approach to mine frequent patterns using item-transformation methods. Information Systems 32, 1056–1072.
Wu, X., & Kumar, V. (2009). The Top Ten Algorithms in Data Mining. Boca Raton: CRC Press.
Xiang, L. (2012). Simulation System of Car Crash Test in C-NCAP Analysis Based on an Improved Apriori Algorithm. Physics Procedia 25 (hal. 2066 – 2071). Elsevier.