Garuda Documents : CORRELATION ANALYSIS OF SENTIMENT OF 2024 ELECTION RESULTS AND STOCK MOVEMENTS OF POLITICAL ACTORS IN INDONESIA

TitleCORRELATION ANALYSIS OF SENTIMENT OF 2024 ELECTION RESULTS AND STOCK MOVEMENTS OF POLITICAL ACTORS IN INDONESIA
Author Order2 of 5
Accreditation2
AbstractGeneral elections (elections) are one of the crucial moments in the political life of a country, where the public democratically elects leaders and their deputies to manage the government. Public sentiment towards the results of elections significantly impacts the political stability and economic conditions of a country. This research aims to analyze the relationship between public sentiment towards the 2024 General Elections in Indonesia and changes in the stock prices of political actors using technological approaches and data analysis. The Long Short-Term Memory (LSTM) method is used to classify sentiment based on Twitter data collected with Harvest Tweet. Evaluation of the LSTM model shows an accuracy rate of 90%, precision of 93.6%, and recall of 92.7%. The correlation analysis using the Spearman coefficient indicates a significant negative relationship with a coefficient of 0.402 and a p-value of 0.046. Implementation of an interactive dashboard using Streamlit facilitates visualization of the data used in this study. Recommendations include increasing the amount of training data for sentiment models, exploring alternative correlation methods for deeper analysis, and refining the interface and data integration on the dashboard to enhance user experience and analysis accuracy. This research is expected to contribute to understanding the dynamics of public sentiment and its impact on the stock market in the context of Indonesian politics.
Publisher NameInformatika, Universitas Jenderal Soedirman
Publish Date2024-08-27
Publish Year2024
DoiDOI: 10.52436/1.jutif.2024.5.4.2701
Citation
SourceJurnal Teknik Informatika (Jutif)
Source IssueVol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Source Page1213-1227
Urlhttp://jutif.if.unsoed.ac.id/index.php/jurnal/article/view/2701/616
AuthorDr LASMEDI AFUAN, S.T, M.Cs
File4549870.pdf