Implementasi Support Vector Machine dalam Analisis Sentimen Ulasan Aplikasi IndiHome TV di Google Play Store

Sentiment analysis is used to determine the responses or opinions of a group or individual regarding a topic of discussion in the context of the entire document. The Indihome TV application is currently widely used by the public, so that reviews of the Indihome TV application on the Google Play Store are very numerous. The exact number of reviews given by users is not yet known based on their sentiment class. Therefore, a method is needed to facilitate the analysis of these user reviews. The purpose of this study is to determine the polarity of sentiment towards the Indihome TV application and to determine the performance and accuracy resulting from the application of the Support Vector Machine algorithm. The method used to convert unstructured reviews into structured reviews uses the Text Mining method. The results of this study indicate that using the SVM algorithm in sentiment analysis of the Indihome TV application data produces the highest accuracy value at a ratio of 90:10 at 94%. Furthermore, from the results of data visualization, the most frequently appearing words are applications, watch, channel, open, please, good, login, indihome, complete and so on.

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Publication Details

Journal
Jurnal SAINTEKOM
Published
2025-09-30
DOI
https://doi.org/10.33020/saintekom.v15i2.954
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Implementasi Support Vector Machine dalam Analisis Sentimen Ulasan Aplikasi IndiHome TV di Google Play Store

Irfan Dwi Jaya, Agus Fajar Riany, Fenny Purwani
Jurnal SAINTEKOM
Data Mining and Machine Learning Applications
article

Implementasi Support Vector Machine dalam Analisis Sentimen Ulasan Aplikasi IndiHome TV di Google Play Store

Irfan Dwi Jaya, Agus Fajar Riany, Fenny Purwani
article en

Abstract

Sentiment analysis is used to determine the responses or opinions of a group or individual regarding a topic of discussion in the context of the entire document. The Indihome TV application is currently widely used by the public, so that reviews of the Indihome TV application on the Google Play Store are very numerous. The exact number of reviews given by users is not yet known based on their sentiment class. Therefore, a method is needed to facilitate the analysis of these user reviews. The purpose of this study is to determine the polarity of sentiment towards the Indihome TV application and to determine the performance and accuracy resulting from the application of the Support Vector Machine algorithm. The method used to convert unstructured reviews into structured reviews uses the Text Mining method. The results of this study indicate that using the SVM algorithm in sentiment analysis of the Indihome TV application data produces the highest accuracy value at a ratio of 90:10 at 94%. Furthermore, from the results of data visualization, the most frequently appearing words are applications, watch, channel, open, please, good, login, indihome, complete and so on.

Jurnal SAINTEKOMVol. 15(2)
Universitas Islam Negeri Raden Intan Lampung (ID)
Openalex Percentile: Top 61%
Data Mining and Machine Learning Applications
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