IMPLEMENTASI CLUSTERING PADA ALGORITMA DBSCAN UNTUK DETEKSI KEJADIAN BENCANA ALAM PADA MICROBLOGGING TWITTER
| Main Author: | M. JUAN SHAPUTRA, 1217051040 |
|---|---|
| Format: | Bachelors NonPeerReviewed Book Report |
| Terbitan: |
FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM
, 2019
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| Subjects: | |
| Online Access: |
http://digilib.unila.ac.id/55994/4/ABSTRAK.pdf http://digilib.unila.ac.id/55994/2/SKRIPSI%20FULL.pdf http://digilib.unila.ac.id/55994/3/SKRIPSI%20TANPA%20BAB%20PEMBAHASAN.pdf http://digilib.unila.ac.id/55994/ |
Daftar Isi:
- Social media is one of media or outlet which uses computer that mainly used by people for giving, sharing, or writing information in any form such as document,image, or video to others using internet connection. Nowadays, many social media offered to people for use, with Twitter being one of them. Twitter is a microblogging social media where its user are capable of writing maximum 140 character of short message which can be embedded with image or video that we called as tweet. In this paper, we focused on detecting tweet that contains word relating to natural disaster, and using clustering method supported by DBSCAN algorithm, we try to cluster them and find the overall similarity value of the cluster, while also seeing the difference of value between cluster which uses classification and cluster which doesn’t use classification. The testing afterwards giving good result, where mainly cluster that uses classification giving bigger overall similarity value.