Sentiment Analysis of Support for the DPR's Right to Inquiry on the Issue of 2024 Election Fraud Using the Support Vector Machine Method

This research aims to analyze public sentiment towards supporting the DPR's right to inquiry in the 2024 Election fraud issue using the Support Vector Machine (SVM) method. Data was obtained from the social media application X which has a wide user base and is relevant to the issue under study. Comments on the application are classified into positive and negative sentiments after going through the pre-processing stage. The SVM method was chosen because of its high ability in text classification based on appropriate kernels. This research shows how much influence the X application has in identifying public sentiment and the effectiveness of the SVM method in sentiment classification. It is hoped that the research results will provide in-depth insight into public sentiment regarding the issue of fraud in the 2024 elections and support better decision making in the context of politics and democracy in Indonesia.

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Publication Details

Journal
Journal La Multiapp
Published
2024-09-01
DOI
https://doi.org/10.37899/journallamultiapp.v5i5.1523
Primary Topic
Indonesian Election Politics and Participation
Type
article
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article

Sentiment Analysis of Support for the DPR's Right to Inquiry on the Issue of 2024 Election Fraud Using the Support Vector Machine Method

Ilka Zufria, Putri Aisyah Sephia
3 links
Journal La Multiapp
Indonesian Election Politics and Participation
article

Sentiment Analysis of Support for the DPR's Right to Inquiry on the Issue of 2024 Election Fraud Using the Support Vector Machine Method

Ilka Zufria, Putri Aisyah Sephia
article en

Abstract

This research aims to analyze public sentiment towards supporting the DPR's right to inquiry in the 2024 Election fraud issue using the Support Vector Machine (SVM) method. Data was obtained from the social media application X which has a wide user base and is relevant to the issue under study. Comments on the application are classified into positive and negative sentiments after going through the pre-processing stage. The SVM method was chosen because of its high ability in text classification based on appropriate kernels. This research shows how much influence the X application has in identifying public sentiment and the effectiveness of the SVM method in sentiment classification. It is hoped that the research results will provide in-depth insight into public sentiment regarding the issue of fraud in the 2024 elections and support better decision making in the context of politics and democracy in Indonesia.

Journal La MultiappVol. 5(5)
Universitas Islam Negeri Sumatera Utara (ID)
Peace, Justice and strong institutions
Openalex Percentile: Top 78%
Indonesian Election Politics and Participation
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Sentiment Analysis of Support for the DPR's Right to Inquiry on the Issue of 2024 Election Fraud Using the Support Vector Machine Method — Ilka Zufria, Putri Aisyah Sephia · Journal La Multiapp (2024) | TGRS Research Map | TGRS