Implementasi Closeness Centrality dalam Analisis Penyanyi Indonesia di DBpedia Indonesia

Nur Aini Rakhmawati (Institut Teknologi Sepuluh Nopember Surabaya)
Ahmad Naufal Muzakki (Institut Teknologi Sepuluh Nopember Surabaya)
Luthfi Lazuardi (Institut Teknologi Sepuluh Nopember Surabaya)

JISKa (Jurnal Informatika Sunan Kalijaga)
Vol. 6 No. 1 (2021): Januari 2021

Indonesian singers have a diverse musical genre. They also origin from several regions in Indonesia. This study analyzes the relationships between singers, genre, and origin of the singer using the Closeness Centrality algorithm. Data are retrieved by using a SPARQL query on DBpedia Indonesia. The generated graph produces a density value of 0.01. The results of the Closeness Centrality calculation shows that more than 50% out of 268 singers had scores above 30%.