Visualization of Information Based on Tweets from Meteorological, Climatological, and Geophysical Agency: BMKG

Mira Chandra Kirana, Amir Amir, Muhammad Nashrullah


Indonesia is a country with high rate of natural disaster, so any information about early warning of natural disaster are very important. Social media such as Twitter become one of tools for spreading information about natural disaster warning from account of  Meteorology, Climatology and Geophysics Agency (BMKG), therefore, the effectiveness of this kind of method for providing information have not known yet. The statement becomes the reason that the visualization is needed to analyze the information spread of natural disaster early warning with Twitter. This study is performed in 3 steps, which is retrieving, preprocessing then visualization. Retrieving process is used to get the tweet data of BMKG account in twitter then save into database, while preprocessing is done to process tweet data that has been saved in database by grouping the data according to the category, which includes Meteorology, Climatology, and Geophysics according to existing keyword, also reduce tweet data that is unimportant like BMKG's reply tweet toward other user's question. Visualization stage uses the result of preprocessing data into line chart graphic, bar chart and pie chart. Highest information spreading from BMKG tweet happened in Geophysics at March with 25987 re-tweets, while the highest peak happened at 2 March 2016 with information about 8.3 SR earthquake in Mentawai islands, West Sumatera with total of 6145 re-tweets.

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JPIT (Jurnal Informatika: Jurnal Pengembangan IT) is licensed under a Creative Commons Attribution 4.0 International License.