ANALISIS AKTOR POPULAR DAN SUTRADARA BERPENGARUH BERDASARKAN DATA DBPEDIA MENGGUNAKAN ALGORITMA CLOSENESS CENTRALITY DAN NODE2VEC - Mufidah, Karima; Syahputra, Novyant; Rakhmawati, Nur Aini (Universitas Komputer Indonesia, 2020)
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