Film Recommendation Analysis with Sequential Pattern Discovery Algorithm Using Equivalence classes (SPADE)

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Aisyah Amini Nur
Akbar Hidayatullah Harahap
Ihsan Muttaqin Bin Abdul Malik
Muhammad Irfan Nur Imam
Muhammad Thariq Sabiq Bilhaq
Angelyna Angelyna

Abstract

Currently, the internet is the most essential thing in human life. So that there is a change in human needs, one of which is enjoying entertainment. With the internet, enjoying entertainment can be done anywhere and anytime, one of the entertainment is movies. With the internet, many service providers provide movie watching sites online. So that people become interested and use it a lot to watch movies online. With the increase in film fans, a film recommendation system is required to make a film recommendation pattern based on previous movie viewing. Therefore, this study aims to provide recommendations for viewing films using the pattern recognition method that often occurs. The technique used is sequence pattern mining using SPADE to find patterns from a group of data. SPADE's advantage is its speed in finding sequence frequencies that can be used as movie recommendation data from previous shows.

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References

Anonymous, “Ketika Pengguna Internet dan Smartphone Terus Meningkat, Android Dominasi Pasar Indonesia,†TribunJabar.id, 2019. http://jabar.tribunnews.com/2019/01/24/ketika-pengguna-internet-dan-smartphone-terus-meningkat-android-dominasi-pasar-indonesia-dan-dunia (accessed Jan. 26, 2019).

Y. Pratomo, “APJII: Jumlah Pengguna Internet di Indonesia Tembus 171 Juta Jiwa,†Kompas.com, 2019. https://tekno.kompas.com/read/2019/05/16/03260037/apjii-jumlah-pengguna-internet-di-indonesia-tembus-171-juta-jiwa (accessed Jul. 14, 2019).

J. Han and M. Kamber, “Data Mining: Concepts and Techniques,†Ann. Phys. (N. Y)., vol. 54, p. 770, 2006, doi: 10.5860/CHOICE.49-3305.

A. C. Raharja, I. S. Sitanggang, and A. Buono, “Purchase Recommendation and Product Inventory Management using Content Based Filtering with Sequential Pattern Mining Approach,†Kinet. Game Technol. Inf. Syst. Comput. Network, Comput. Electron. Control, pp. 287–294, 2018, doi: 10.22219/kinetik.v3i4.663.

D. A. Saputra, E. T. Tosida, and F. D. W, “PENENTUAN POLA SEKUENSIAL DATA TRANSAKSI PENJUALAN MENGGUNAKAN ALGORITMA SEQUENTIAL PATTREN DISCOVERY USING EQUIVALENT CLASSES (SPADE),†Komputasi J. Ilm. Ilmu Komput. dan Mat., vol. 16, no. 2, pp. 271–282, 2019, doi: 10.33751/komputasi.v16i2.1621.

D. Yunianto, C. Dewi, S. Kom, and N. Yudistira, “Sequential Pattern Mining Pada Pencarian Pola Perilaku Penggunaan Internet Menggunakan Algoritma SPADE.†Universitas Brawijaya, 2014.

F. Ricci, B. Shapira, and L. Rokach, “Recommender systems: Introduction and challenges,†in Recommender Systems Handbook, Second Edition, 2015, pp. 1–34.

R. Agrawal and R. Srikant, “Fast Algorithms for Mining Association Rules in Large Databases,†J. Comput. Sci. Technol., vol. 15, no. 6, pp. 487–499, 1994, doi: 10.1007/BF02948845.

M. J. Zaki, “SPADE: An efficient algorithm for mining frequent sequences,†Mach. Learn., vol. 42, no. 1–2, pp. 31–60, 2001, doi: 10.1023/A:1007652502315.