The Frequent Pattern Growth Algorithm in the Film Recommendation System
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pattern mining,
recomendation system
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Abstract
In order to decrease the covid-19 rate, people choose to stay at home. Watching movies with family can be an alternative to fill activities during a pandemic. But sometimes it’s hard to determine the film to be watched. To overcome this a recommendation system is needed. This research is shown to build a system recommendation for film recommendations next will be witnessed. This system created using the Frequent Pattern Growth Algorithm which will do filtering later against several films based on the user’s viewing history. The results of testing the recommendation system using the FP-Growth algorithm work well and can show a minimum support value of 0.973 and a confidence value of 0.291, where the size of this value affects the resulting pattern output.
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References
T. O. Wibowo, “Fenomena Website Streaming Film di Era Media Baru: Godaan, Perselisihan, dan Kritik (The Phenomena of Movie Streaming Websites in New Media Era: Temptation, Disputes, and Critique),†J. Kaji. Komun., vol. 6, no. 2, p. 191, 2018, [Online]. Available: http://jurnal.unpad.ac.id/jkk/article/view/15623.
A. Kusnadi, C. K. Widiarso, and H. Hugeng, “Rancang Bangun Sistem Rekomendasi Pemilihan Smartphone Berbasis Web,†J. Ultim. InfoSys, vol. 7, no. 1, pp. 31–37, 2017, doi: 10.31937/si.v7i1.510.
A. E. Wijaya and D. Alfian, “Sistem Rekomendasi Laptop Menggunakan Collaborative Filtering Dan Content-Based Filtering,†J. Comput. Bisnis, vol. 12, no. 1, pp. 11–27, 2018.
J. Maximillian, H. N. Palit, and A. N. Tjondrowiguno, “Sistem Rekomendasi Film Menggunakan Integrated Kohonen K-Means clustering,†J. Infra, vol. 8, no. 1, pp. 19–25, 2020.
R. Yanto and R. Khoiriah, “Implementasi Data Mining dengan Metode Algoritma Apriori dalam Menentukan Pola Pembelian Obat,†Creat. Inf. Technol. J., vol. 2, no. 2, p. 102, 2015, doi: 10.24076/citec.2015v2i2.41.
R. Fitria, W. Nengsih, and D. H. Qudsi, “Implementasi Algoritma FP-Growth Dalam Penentuan Pola Hubungan Kecelakaan Lalu Lintas,†J. Sist. Inf., vol. 13, no. 2, p. 118, 2017, doi: 10.21609/jsi.v13i2.551.
N. L. G. P. Suwirmayanti, “Penerapan Metode K-Nearest Neighbor Untuk Sistem Rekomendasi Pemilihan Mobil,†Techno.Com, vol. 16, no. 2, pp. 120–131, 2017, doi: 10.33633/tc.v16i2.1322.
A. Maulana and A. A. Fajrin, “PENERAPAN DATA MINING UNTUK ANALISIS POLA PEMBELIAN KONSUMEN DENGAN ALGORITMA FP-GROWTH PADA DATA TRANSAKSI PENJUALAN SPARE PART MOTOR,†KLIK - Kumpul. J. ILMU Komput., vol. 5, no. 1, p. 27, 2018, doi: 10.20527/klik.v5i1.100.
R. Nurul Arifin, “Implementasi Algoritma Frequent Pattern Growth (FP-GROWTH) Menentukan Asosiasi Antar Produk (Study KAsus Nadia Mart),†J. Tek. ITS, pp. 68–76, 2015.
Erwin, “Analisis Market Basket Dengan Algoritma,†J. Generic, vol. 4, pp. 26–30, 2009.
H. Jiawei, M. Kamber, J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques. 2006.
F. Fitriyani, “IMPLEMENTASI ALGORITMA FP-GROWTH MENGGUNAKAN ASSOCIATION RULE PADA MARKET BASKET ANALYSIS,†J. Inform., vol. 2, no. 1, 2016, doi: 10.31311/ji.v2i1.85.