Authors:

Karlina Surya Witanto, Ngurah Agus Sanjaya ER, AAIN Eka Karyawati, I Gusti Agung Gede Arya Kadyanan, I Ketut Gede Suhartana, Luh Gede Astuti

Abstract:

“Movies are an entertainment that is in great demand by many groups from children, teenagers, adults, and parents. In the current digital era, various films can be watched on television to digital streaming services. Public opinion on the films watched can be in the form of positive opinions or negative opinions. Sentiment analysis is one of the fields of Natural Language Processing (NLP) which is able to build a system to recognize and extract opinions in the form of text, sentiment analysis is usually used to find out people’s opinions or assessments of a products, services, politics, or other topics. Through sentiment analysis from the collection of reviews, the public can get various recommendations for films that can be watched. The method implemented to classify review data into positive reviews and negative reviews in this study is LSTM by comparing two different optimizers, namely Adam and RMSprop. This study succeeded in providing sentiment predictions with different optimizers with accuracy values ??for the LSTM application with Adam Optimizer reaching 77.11% and the LSTM application with RMSprop reaching 80.07%.”

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PDF:

https://jurnal.harianregional.com/jlk/full-86119

Published

2022-06-13

How To Cite

WITANTO, Karlina Surya et al. Implementasi LSTM Pada Analisis Sentimen Review Film Menggunakan Adam Dan RMSprop Optimizer.JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 10, n. 4, p. 351-362, june 2022. ISSN 2654-5101. Available at: https://ojs.unud.ac.id/index.php/JLK/article/view/86119. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/JLK.2022.v10.i04.p05.

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ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian

Issue

Vol 10 No 4 (2022): JELIKU Volume 10 No 4, May 2022

Section

Articles

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License