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All Journal International Journal of Electrical and Computer Engineering JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Creative Information Technology Journal INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Pilar Nusa Mandiri Syntax Literate: Jurnal Ilmiah Indonesia Technomedia Journal EXPLORE M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Journal of Information Systems and Informatics Jurnal Tecnoscienza Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat MEANS (Media Informasi Analisa dan Sistem) Information System Journal (INFOS) Intechno Journal : Information Technology Journal
Anggit Dwi Hartanto, Anggit Dwi
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Journal : M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika

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Comparison of LSTM and GRU Methods in Sentiment Analysis of Satusehat Appication Review Hedy Leoni; Utami, Ema; Hartanto, Anggit Dwi
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 8 No. 3 (2023): Mathline: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v8i3.475

Abstract

This article describes a comparison between the LSTM and GRU methods in sentiment analysis. Both methods were chosen based on the simplicity of the model and are considered capable of processing relatively long data. the dataset used in this study amounted to 12260 data obtained from scraping on the Google Play site using google-play-scraper library. In analyzing Sentiments, 2 Deep Learning methods are used, namely LSTM and GRU. From the results The GRU accuracy value reaches 91% while the LSTM accuracy value is 89%. However, for the Recall and F1-score tests, these two methods still get low scores in analyzing positive data.
Co-Authors Adiatma, Biva Candra Lutfi Adipradana, Candra Ananda, Fadhilah Dwi arif nur rohman Arif Santoso ATIK NURMASANI Christyawan, Fajar Ema Utami Fajri, Ika Nur Fiardin, Tsintani Tisaga Fitriyani, Nurul Khasanah Hartatik Hedy Leoni Hidayat, Jati Arif Idris Idris Julianto, M. Rayhan Wahyu Kanoena, Melcior Paitin Kencana, Adi Kresna Khairullah, Irfan Khalil Kurniawan, Aas Andri Kurniawan, Febri Dwi Kusnawi Kusnawi Pattimura, Yudha Bagas Pratama, Jibran Yoga Purwoko, Joshua Dwi Giovani Ramadhan, Muhammad Jauharul Ramadhani, Zanuarestu Rasyid, Muhammad Khulqi Safira, Livia salisah, Tuhfatus Sari, Bunga Permata Setiadi F., A. Farhan Setiawan, Annas Setiawanda, Yongky Budi Suwanto Raharjo Syahrudin, Erwin Tara, Yudi Tuhpatussania, Siti wahyuni, wenti ayu Wasistha, Dyah Wicaksono, Anggito Whiku Wisnu Nugroho Aji, Wisnu Nugroho Yulianto, Yogi Yusa, Aldo