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All Journal JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP)
Chuanta, Roy Vidia
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Computer Science & IT

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Penggunaan Recurrent Neural Network Dalam Mendeteksi Sentimen Berbahaya Pada Platform Media Sosial Chuanta, Roy Vidia; Harahap, Mawaddah; Putra, Adya Zizwan
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 7 No. 1 (2024): Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v7i1.4845

Abstract

Social media platforms in today's modern era make it easier for people to communicate and socialize. Behind that, on a hot topic, there must be sentiment. Every sentiment the community conveys varies; some are good and neutral, and some are bad or dangerous. To detect sentiment, start from crawling data, pre-processing, labeling, and then testing or training to get accuracy value, recall value, f1 value, and precision value using Long Short Term Memory. They obtained an accuracy value of 0.582, recall value of 0.582, f1 value of 0.428, and precision of 0.339. This LSTM model can be used to develop an analysis model that is successfully achieved.
Co-Authors Mawaddah Harahap, Mawaddah Putra, Adya Zizwan