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All Journal Jurnal Buana Informatika Jurnal Informatika Universitas Pamulang International Journal of Computer and Information System (IJCIS) Advance Sustainable Science, Engineering and Technology (ASSET) Electron: Jurnal Ilmiah Teknik Elektro Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Ilmiah Informatika dan Ilmu Komputer Jurnal Rekayasa Sistem Informasi dan Teknologi Journal of Information Systems Management and Digital Business
Prayogo, Johan Suryo
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Social Sciences

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Implementation of Text Processing Techniques on Citizen Opinions Regarding Floods in Surabaya kriswibowo, rony; Alia, Putri Ariatna; Prayogo, Johan Suryo; Febriana, Rusina Widha
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 5 No 1: Jurnal Electron, Mei 2024
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v5i1.148

Abstract

An analysis of residents opinions on flooding in Surabaya is essential to identify their perceptions and aspirations towards this disaster. This can facilitate the making of appropriate flood mitigation policies. The current problem is that it is difficult to retrieve data from X in the form of both users and tweets automatically. So that in some studies that use tweet data becomes less efficient in the data collection process. This research confirmed the use of messages to determine highly impactful disaster zones and showed how tweets can be used to identify oscillations in disaster intensity over time. The topic of this research is to apply the Data Crawling method to obtain datasets on social media X. Then the next method is text preprocessing using Wordcloud, Matplotlib, (NTLK) Natural Language Toolkit, and Sastrawi libraries. In natural language processing, the data to be extracted includes unstructured or “arbitrary” data. In normal dialect preparing (NLP), the information to be extracted includes unstructured or "self-assertive" information.  For future purposes (assumption examination, subject modeling, etc.), such information must be changed over into organized data. The discoveries of the think about can help the organization in comprehending the necessities and inclinations of the people with respect to surges. This article demonstrates how Artificial Intelegence may be applied to text data analysis in order to provide insightful findings. the outcomes of this research can help the government in making more effective policies to overcome flooding in Surabaya
Co-Authors Agung Budi Setyawan, Agung Budi Alia, Putri Ariatna Cahyono, Warna Agung Febriana, Rusina Widha Kriswibowo, Rony Lieztyanto, Yeeryzkhe Githasari Pratama, Setya Budi Putri Ariatna Alia Setyadi, Agung Teguh Setyohadi, Djoko Budiyanto