Abstract

The 2019 general election in Indonesia aims to elect the President and Vice President, Legislative Assembly (DPR and DPRD), and Regional Representative Council (DPD). The candidates must fill out their personal data in the general election official website at the time of registration. We perform the Social Network Analysis (SNA) over legislative candidate data to determine the pattern of relationships between candidates based on these data. The community detection algorithms in SNA can map and illustrate the pattern of relationship that is owned by the candidates in the 2019 elections. The output of this analysis will be visualized in graphs to illustrate the pattern of relationships based on the results of the SNA algorithm calculation. Based on the calculation of community detection algorithms, 60 communities were consisting of two to four candidates.

Original languageEnglish
Title of host publication2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020
EditorsIndra Hermawan, Muhammad Yusuf Bagus Rasyidin, Malisa Huzaifa, Iklima Ermis Ismail, Asep Taufik Muharram, Anggi Mardiyono, Noorlela Marcheeta, Dewi Kurniawati, Ade Rahma Yuly, Ariawan Andi Suhanda
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages306-310
Number of pages5
ISBN (Electronic)9781728182476
DOIs
Publication statusPublished - 15 Sept 2020
Event3rd International Conference on Computer and Informatics Engineering, IC2IE 2020 - Depok, Indonesia
Duration: 15 Sept 202016 Sept 2020

Publication series

Name2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020

Conference

Conference3rd International Conference on Computer and Informatics Engineering, IC2IE 2020
Country/TerritoryIndonesia
CityDepok
Period15/09/2016/09/20

Keywords

  • 2019 general election
  • community detection
  • legislative candidates
  • social network analysis

Fingerprint

Dive into the research topics of 'Social Network Analysis of Legislative Candidates in Indonesia General Election 2019 Using Community Detection'. Together they form a unique fingerprint.

Cite this