PENGGEROMBOLAN TWEET BADAN NASIONAL PENANGGULANGAN BENCANA INDONESIA PERIODE AGUSTUS 2018 FEBRUARI 2019 MENGGUNAKAN TEXT MINING
Keywords:clustering analysis, disaster, k-means, text mining
Twitter is a popular social media platform for communicating between its users by writing short messages in limited characters, called tweets. Extracting data information that has non-structured form and huge-sized, usually known as text mining. Badan Nasional Penanggulangan Bencana Indonesia (@BNPB_Indonesia) is the official twitter account of the government agency in the field of disaster management that uses twitter to share much information about disasters that have occurred in Indonesia. This study aims to determine the characteristics of all tweets and to group the types of tweets that they shared based on the similarity of its content. The data used in the study came from BNPB Indonesia's tweets with the period of taking tweets 6th of August 2018 to 16th of February 2019. The cluster result obtained by the k-Means method was 4 groups. The characteristics of the first cluster contained information about the weather conditions in Yogyakarta, the second cluster was about the source and magnitude of an earthquake, and the third group was about the occurrence of earthquakes in Lombok. However, the fourth group characteristic couldn’t be specifically identified because there was no clear distinction between other tweets in its members.
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