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Muhammad Akram Mansyur
Erasmus Rotterdam University, Netherlands

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COMMUNICATION NETWORKS ANALYSIS ON INFORMATION DISSEMINATION OF THE MOVING OF CAPITAL CITY FROM JAKARTA TO EAST KALIMANTAN Kiayati Yusriyah; Sudaryanto Sudaryanto; Ahmad Fatoni; Muhammad Akram Mansyur
ASPIRATION Journal Vol. 1 No. 1 (2020): July Edition of ASPIRATION Journal
Publisher : ASPIKOM Jabodetabek Region

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Abstract

Jakarta as the state capital of Indonesia faces complex problems in daily life, especially those related to high population density, urbanization, traffic congestion, natural disasters, and severe environmental conditions. These problems are becoming justifications for the need to move the country's capital to East Kalimantan as decided by the government. East Kalimantan was chosen as the new capital, based on the results of intensive studies, having very minimal disaster reserves such as floods, earthquakes, tsunamis, forest fires and landslides. East Kalimantan is also considered to have a strategic location. If drawn coordinates, its location is in the middle of Indonesian territory, and is near urban areas. Dissemination of information about those planning is done through various communication networks, including on social media. This study aims to identify the dominant actors in communication networks on Twitter with the hashtag #IbuKotaBaru during the periods of August 1 to September 22, 2019. The study was conducted using quantitative approach by employing GEPHI tools. The results revealed that in the #IbuKotaBaru communication network, there were three dominant actors who actively disseminate the relevant information namely detikfinance, yulionta and derupiston. The most popular actor was detikfinance. There are 63.33% of actors who have a high closeness with other actors, there are no actor who mediate with other actors in communication. Yulionta and Derupiston are the two most important actors in disseminating information about the move to new country’s capital in the #IbuKotaBaru communication network as indicated by its highest values of Eigenvector Centrality.