Authors:

Alim Ikegami, I Dewa Made Bayu Atmaja Darmawan

Abstract:

“In recent years, audio content has seen a rise in consumption. The COVID-19 pandemic also contributes to the rise in consumption. In the survey that was conducted in 2021, more than 40% of people in France, Germany, and Spain have been listening to more audio content since the first restriction on COVID-19 came into place [1]. One of the rising startups in Indonesia that offers audio content with their original and exclusive content is Noice. To maintain their quality of service, it’s important to look into the reviews that were written for their application. To analyze the reviews, sentiment analysis and topic modeling can be used to extract the sentiment polarity and the topics that are discussed on each sentiment polarity [3]. In this study, XGBoost and Latent Dirichlet Allocation are used to analyze the reviews that were written in Google Play Store. The result of the sentiment analysis yielded accuracy, precision, recall, and F1-score of 87,5%, 84,8%, 79,4%, and 81,6%. While the topic modeling managed to extract 16 and 6 topics respectively for positive and negative reviews.”

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PDF:

https://jurnal.harianregional.com/jnatia/full-92679

Published

2022-11-25

How To Cite

IKEGAMI, Alim; DARMAWAN, I Dewa Made Bayu Atmaja. Analisis Sentimen dan Pemodelan Topik Ulasan Aplikasi Noice Menggunakan XGBoost dan LDA.Jurnal Nasional Teknologi Informasi dan Aplikasnya, [S.l.], v. 1, n. 1, p. 325-336, nov. 2022. ISSN 3032-1948. Available at: https://jurnal.harianregional.com/jnatia/id-92679. Date accessed: 08 Jul. 2024.

Citation Format

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 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022

Section

Articles

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