CLUSTERING DATA FILM DAN SERIES NETFLIX MENGGUNAKAN METODE K-MEANS DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING

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Nathaniel Andrew

Abstract

Films and series on Netflix can be clustered by genre, country of origin and theme. Clusters based on genre can help users find films or series that suit their interests. Clusters based on country of origin can help users find works from various countries. Theme-based clusters can help users find films or series that cover certain themes. Clustering films and series on Netflix can help users find shows that suit their interests and needs. This can increase user satisfaction with Netflix services.

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References

[1] Burhanuddin, Zainudin. "Penerapan Metode Agglomerative Hierarchical Clustering dengan Validator Silhouette Index." Skripsi 1.413416016 (2020).

[2] Dhuhita, W. M. P. (2015). Clustering Menggunakan Metode K-Means Untuk Menentukan Status Gizi Balita.

[3] Suhirman, Suhirman, and Hero Wintolo. "System for Determining Public Health Level Using the Agglomerative Hierarchical Clustering Method." Compiler 8.1 (2019): 95-104.

[4] Gustientiedina, G., Adiya, M. H., & Desnelita, Y. (2019). Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan.

[5] Sulastri H, Gufroni AI. Penerapan Data Mining Dalam Pengelompokan Penderita Thalassaemia. Jurnal Teknologi dan Sistem Informasi. 2017.

[6] Priyatman, H., Sajid, F., & Haldivany, D. (2019). Klasterisasi Menggunakan Algoritma K-Means Clustering untuk Memprediksi Waktu Kelulusan Mahasiswa

[7] Ningrat, D. R., Di Asih, I. M., & Wuryandari, T. (2016). Analisis cluster dengan algoritma K-Means clustering untuk pengelompokan data obligasi korporasi.

[8] Wilson, Wilson. "Website Klasifikasi Jurnal Berdasarkan Abstrak Dengan Metode Agglomerative Hierarchical Clustering", Jurnal Ilmiah Core IT: Community Research Information Technology 11.4 (2023).

[9] Alfariz, Riki. "Implementasi Metode Agglomerative Hierarchical Clustering Untuk Pengelompokkan Jurnal Berdasarkan Abstrak Berbasis Website." KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) 6.1 (2023): 700-706.

[10] Setyawan, Dimas Ari, and Chastine Fatichah. "Enhancement of Decission Tree Method Based on Hierarchical Clustering and Dispersion Ratio." JUTI: Jurnal Ilmiah Teknologi Informasi 18.2 (2020): 179-187.

[11] Muflihan, Yenni, Heri Retnawati, and Agus Kistian. "Analisis cluster dengan metode hierarki untuk pengelompokan sekolah menengah atas berdasarkan raport mutu sekolah di Kabupaten Nagan Raya." Measurement In Educational Research 2.1 (2022): 22-33.

[12] Adek, Rizal Tjut, Rozzy Kesuma Dinata, and Ananda Ditha. "Online Newspaper Clustering in Aceh using the Agglomerative Hierarchical Clustering Method." International Journal of Engineering, Science and Information Technology 2.1 (2022): 70-75.

[13] Ula, Mutammimul, et al. "Implementation of Machine Learning in Determining Nutritional Status using the Complete Linkage Agglomerative Hierarchical Clustering Method." Jurnal Mantik 5.3 (2021): 1910-1914.

[14] Nofiar, Andri, and Sarjon Defit. "Penentuan Mutu Kelapa Sawit Menggunakan Metode K-Means Clustering." Jurnal KomtekInfo 5.3 (2018): 1-9.

[15] Anjelita, Mawaddah, et al. "Analisis Metode K-Means pada Kasus Ekspor Barang Perhiasan dan Barang Berharga Berdasarkan Negara Tujuan." Seminar Nasional Sains dan Teknologi Informasi (SENSASI). Vol. 2. No. 1. 2019.

[16] Dewi, Sinta Maulina, et al. "Analisa Metode K-Means pada Pengelompokan Kriminalitas Menurut Wilayah." Seminar Nasional Sains dan Teknologi Informasi (SENSASI). Vol. 2. No. 1. 2019.Teknologi Informasi dan Komputer) 6.1 (2023): 700-706.

[17] Sari, Riyani Wulan, and Dedy Hartama. "Data Mining: Algoritma K-Means Pada Pengelompokkan Wisata Asing ke Indonesia Menurut Provinsi." Seminar Nasional Sains dan Teknologi Informasi (SENSASI). Vol. 1. No. 1. 2018.

[18] Sembiring, Muhammad Ardiansyah, Raja Tama Andri Agus, and Mustika Fitri Larasti Sibuea. "Penerapan Metode Algoritma K-Means Clustering Untuk Pemetaan Penyebaran Penyakit Demam Berdarah Dengue (DBD)." Journal of Science and Social Research 4.3 (2021): 336-341.

[19] Rozaq, Abdul. "Implementation of K-Means and Agglomerative Hierarchical Methods to House Clusterization." Jurnal Media Informatika Budidarma 6.2 (2022): 933-942.

[20] Azmi, Mardhiatul, et al. "Comparison of the Performance of the K-Means and K-Medoids Algorithms in Grouping Regencies/Cities in Sumatera Based on Poverty Indicators." UNP Journal of Statistics and Data Science 1.2 (2023): 59-66.