TWEET CLASSIFICATION USING DEEP LEARNING ARCHITECTURE FOR CONCERT EVENT DETECTION

Adenuar Purnomo (Institut Teknologi Sepuluh Nopember)
Ahmad Afiif Naufal (Institut Teknologi Sepuluh Nopember)
Ery Permana Yudha (Institut Teknologi Sepuluh Nopember)
Agus Zainal Arifin (Institut Teknologi Sepuluh Nopember)

Jurnal Ilmu Komputer dan Informasi
Vol 13, No 2 (2020): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information

Twitter social media is used by millions of users to share stories about their lives. There are millions of tweets sent by Twitter users in a short amount of time. These tweets can contain information about an incident, complaints from Twitter users, and others. Finding information about events from existing tweets requires great effort. Therefore, this study proposed a system that can detect events based on tweets using the CNN-LSTM architecture. Based on the classification testing obtained precision results of 70.97%, and recall amounted to 63.76%. The results obtained are good enough as a first step to detect events on Twitter.