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All Journal Jurnal E-bussiness Institut Teknologi dan Bisnis Muhammadiyah Polewali Mandar Journal of Governance and Public Administration Jurnal Intelek Insan Cendikia International Journal of Computer Technology and Science
Arya Saputra
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : International Journal of Computer Technology and Science

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Sentiment Analysis Of Social Media Data Using Deep Learning Techniques Salsabila Septiani; Nabila Putri; Dara Jessica; Arya Saputra
International Journal of Computer Technology and Science Vol. 1 No. 2 (2024): April : International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i2.59

Abstract

Social media platforms contain vast amounts of data that can reveal public sentiment on various topics. This research explores the application of deep learning techniques, particularly convolutional neural networks (CNN) and recurrent neural networks (RNN), to analyze sentiment within social media text. The results indicate that these models achieve high accuracy in sentiment classification, making them valuable tools for companies seeking to understand public opinion.
Co-Authors Abdul Mughaffar Asfani Adyka Putra Bagus Kautsar Albar Kresna Lukito Nugroho Ali Imran Anisa Yusri Ramdhani Ariibah Zain Bahiirah Azahra, Friska Anggita Dara Jessica Fressyana Kusuma Ratri Jazuli Abdin Munib Joko Tri Nugraha Marawiah Maya Ramadhani Muhammad Faizal Amri Muhammad Tristan Ath Thaariq Mutia Ensa Syazwina Nabila Putri Naufal Fathi Ardhana Sahabudin, Arfah Salmayunicha Listie Putri Salsabila Septiani Siti Asisyah Suci Wulandari