<![CDATA[In Indonesia, there have been several naturaldisasters, such as earthquakes, tsunamis, landslides, floods, andothers. Because Indonesia is situated where the Eurasian,Pacific, and Indo-Australian plates converge, this potentialnatural disaster is caused by this location. Social mediainformation is expanding quickly and becoming more useful.Social media helps to alert people of the disaster's locationduring a disaster like a flood. Twitter is used as a data searchengine in this work. Twitter has been utilized effectively toupdate the public on current events during emergencies. Inorder to learn more, we can conduct a search using pertinenthashtags to determining for the incident's location. The test'sresults will show a map of the Indonesian region, and thedisaster's epicenter will be determined using the geolocationprovided by the tweet data. The Naive Bayes approach will beused for classification. The clustering process occurs in real timeacross every region of Indonesia. In this investigation, theaccuracy value was 75% based on the k-fold cross-validationtest, utilizing a fold value of 3. Keywords—Natural disasters, Twitter, Naïve Baiyes.]]>
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