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Submitted
Jun 7, 2024
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Dec 31, 2024
Published
Dec 31, 2024
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Abstract

The twitter social network is widely used to discuss all kinds of topics, including those related to politics. Analyzing online conversations on Twitter to map the popularity of political figures as candidates for the Indonesian presidential election is a popular and challenging research area. In the Twitter network, citizens can express themselves and communicate with political figures. The conversational data in Twitter is very complex, so Business Intelligence is needed to transform raw data into meaningful and useful information to see the popularity of Indonesian presidential election candidates. The analysis used is Social Network Analysis (SNA) by measuring Degree Centrality, Eigenvector Centrality, Betweenness Centrality, Closeness Centrality. The presidential candidates in this study, Ganjar Pranowo with a twitter account “ganjarpranowo”, Puan Maharani with a twitter account “puanmaharani_ri”, and Anies Baswedan with a twitter account “aniesbaswedan”. The actor "aniesbaswedan" excels in the value of degree centrality and betweenness centrality. The “aniesbaswedan” account is the actor who has the most influence on social network interactions based on the total number of interactions generated, then the account also becomes a bridge or liaison in the interactions of other actors in the network.

Keywords

centrality degree density SNA

Article Details

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How to Cite
Ali, I., & Girsang, A. S. (2024). BUSINESS INTELLIGENCE (BI) PRESIDENTIAL CANDIDATES BASED ON SOCIAL NETWORK ANALYSIS (SNA) WITH TWITTER DATA. Parameter: Journal of Statistics, 4(2), 54-64. https://doi.org/10.22487/27765660.2024.v4.i2.17143

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