ANALISIS AKTOR POPULAR DAN SUTRADARA BERPENGARUH BERDASARKAN DATA DBPEDIA MENGGUNAKAN ALGORITMA CLOSENESS CENTRALITY DAN NODE2VEC
DOI:
https://doi.org/10.34010/miu.v18i1.3836Abstract
The rapid development of web technology makes it easier for humans to access various information. The third generation of web-based internet services (Web 3.0) has introduced the Semantic Web which aims to enable content on the web to be understood by computers. The application of semantic web can be done to retrieve a dataset from Dbpedia Indonesia, which is a list of Indonesian films, for further data analysis. The purpose of data analysis is to find out the most popular actors and directors in the Indonesian film industry. This study uses closeness centrality and Node2vec algorithms to determine the level of popularity of actors. In addition, this study also uses density graph to determine the influential directors in the Indonesian film industry. The results of the algorithm calculations are visualized using Neo4j, Networkx, and tSNE which are graphs. In this study it was found that Rima Melati was the most popular actor because of the highest closeness centrality value. This can also be interpreted that Rima Melati is an actor who starred in the most films. While in density graph calculation, Sophan Sophiaan is the most influential director because he directs the most movie titles.
Key Words : closeness centrality, dbpedia, density graph, networkx, node2vec
References
A. Nurwahdah, “Sistem Tanya Jawab dengan Web Semantik,†in Seminar Nasional Aplikasi Teknologi Informasi (SNATI), 2015, vol. 1, no. 1.
Y. F. Badron, F. Agus, and H. R. Hatta, “STUDI TENTANG PEMODELAN ONTOLOGI WEB SEMANTIK DAN PROSPEK PENERAPAN PADA BIBLIOGRAFI ARTIKEL JURNAL ILMIAH,†in Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi), 2017, vol. 2, no. 1, pp. 164–169.
A. Rochiyat and A. Wibowo, “Analisis Aktor Berpengaruh Dan Aktor Popular Dengan Metode Degree Centrality Dan Follower Rank Pada Tagar Twitter ‘# gejayanmemanggil,’†JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 6, no. 2, pp. 130–138, 2020.
M. S. Setatama and D. Tricahyono, “Implementasi Social Network Analysis pada Penyebaran Country Branding ‘Wonderful Indonesia,’†Indones. J. Comput., vol. 2, no. 2, pp. 91–104, 2017.
J. B. Sanawi, M. C. Samani, and M. Taibi, “# vaccination: Identifying influencers in the vaccination discussion on twitter through social network visualisation,†Int. J. Bus. Soc., vol. 18, no. S4, pp. 718–726, 2017.
I. Gialampoukidis, G. Kalpakis, T. Tsikrika, S. Papadopoulos, S. Vrochidis, and I. Kompatsiaris, “Detection of terrorism-related twitter communities using centrality scores,†in Proceedings of the 2nd International Workshop on Multimedia Forensics and Security, 2017, pp. 21–25.
R. Oktora and A. Alamsyah, “Pola Interaksi dan Aktor yang Paling Berperan pada Event JGTC 2013 melalui Media Sosial Twitter (Studi Menggunakan Metode Social Network Analysis),†J. Manaj. Indones., vol. 14, no. 3, pp. 201–209, 2014.
The W3C SPARQL Working Group, “SPARQL 1.1 Overview. W3C Recommendation 21 March 2013,†W3C, 2013. .
A. Grover and J. Leskovec, “node2vec: Scalable feature learning for networks,†in Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data mining, 2016, pp. 855–864.
M. Needham and A. E. Hodler, Graph Algorithms: Practical Examples in Apache Spark and Neo4j. O’Reilly Media, 2019.
R. kumar Kaliyar, “Graph databases: A survey,†in International Conference on Computing, Communication & Automation, 2015, pp. 785–790.
A. Hagberg, P. Swart, and D. S Chult, “Exploring network structure, dynamics, and function using NetworkX,†Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2008.
L. van der Maaten and G. Hinton, “Visualizing data using t-SNE,†J. Mach. Learn. Res., vol. 9, no. Nov, pp. 2579–2605, 2008.
N. Tatti, “Density-friendly graph decomposition,†ACM Trans. Knowl. Discov. from Data, vol. 13, no. 5, pp. 1–29, 2019.
“Daftar Film Indonesia.†http://id.dbpedia.org/page/Daftar_film_Indonesia.
novyantsp, “novyantsp/notebook-tweb: Notebook Tweb,†May 2020, doi: 10.5281/ZENODO.3839044
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