Indonesian Presidential Election Research Articles

Sentiment Classification on the 2024 Indonesian Presidential Candidate Dataset Using Deep Learning Approaches

This study aims to compare the performance of three deep learning models (LSTM, BiLSTM, and GRU) in the task of sentiment classification for the 2024 Indonesian Presidential Candidate dataset, focusing specifically on the case of Prabowo Subianto. The dataset comprises social media X posts sourced from kaggle, and the analysis investigates the effectiveness of different variants of recurrent neural network architectures in identifying public sentiment. The models were evaluated on accuracy and F1 score. The results demonstrate that BiLSTM outperformed both LSTM and GRU models in all metrics, achieving a testing accuracy of 80.70% and an F1 score of 86.86%, compared to LSTM and GRU which both achieved a testing accuracy of 72.56% and an F1 score of approximately 84%. The higher performance of BiLSTM is attributed to its ability to capture bidirectional context within the text, thereby understanding complex sentiment patterns more effectively. LSTM and GRU models displayed similar performance, therefore BiLSTM is the best model for this dataset. These results indicate that BiLSTM is especially well-suited for analyzing public sentiment towards political figures like Prabowo Subianto, offering significant insights into public discussions surrounding the 2024 Indonesian Presidential Election. This study recommends exploring transformer-based models like BERT or GPT variants to enhance sentiment classification accuracy in this domain.

Dissecting the Political Persona of the 2024 Indonesian Presidential Election through Visual Framing Analysis

Public interest in political battles is constant, and the Indonesian presidential election in February 2024 is no exception. The three presidential candidates, who have been declared, aggressively establish their political personas and gain exposure and notoriety using Instagram, including @aniesbaswedan, @ganjar_pranowo, and @prabowo. This study aims to dissect the political persona of the 2024 Indonesian presidential candidates using the visual framing analysis method, studying how certain points of view are emphasized or made prominent through visual messages. While other framing studies focus on textual analysis, visual framing analysis is rarely employed even though visual elements have the power to build emotional affection and can last longer in memory. The study's data set comprises Instagram posts from the officially declared presidential contender (@aniesbaswedan from October 3, 2022; @ganjar_pranowo from April 21, 2023; @prabowo from August 12, 2022) to May 21, 2023. The research findings indicate that the political persona built by each presidential candidate still revolves around aspects of their own inherent identity such as religion, race, ethnicity, tribe, customs, habits, education level, economic status, social status, family background, and political stance, rather than providing a clear picture of their priority policy programs when in office.

PRABOWO SUBIANTO'S EUPHEMISM USED IN THE 2024 PRESIDENTIAL ELECTION DEBATE

Prabowo Subianto is one of the 2024 presidential candidates participating in the Indonesian presidential election debate organized by the General Elections Commission (KPU). This debate features polite and non-offensive language, reflecting the use of euphemisms. This research aims to uncover the hidden practices in the use of euphemisms that Prabowo Subianto applied during the debate. A descriptive qualitative approach was employed, with the data consisting of orthographic transcriptions of his utterances. The data were collected through the observation method, advanced note-taking techniques, and documentation. The analysis was conducted using Content Analysis with Krippendorff's framework, which includes sampling, recording, and context units. The findings reveal ten types of euphemisms used by Prabowo Subianto, with loanwords being the most dominant, followed by hedges, overstatements, litotes, periphrasis, metaphors, downtoners, underspecification, apologetic expressions, and understatements. The study also identified eight main functions of euphemisms, and the most dominant function is being self-promotion, followed by protecting uncertain statements, as well as reducing hostility. This research enriches linguistic studies, particularly in the field of pragmatics, by demonstrating how various types of euphemisms are used in political communication.

Democracy in the face of identity politics: Indonesian citizens’ perspectives

ABSTRACT This study investigates the role of religious orientation in shaping voter behavior in Madura during the 2019 Indonesian presidential election. Employing a mixed-method approach, the research examines how Islamic identity politics influenced voter preferences in a region characterized by religious homogeneity. The study finds that while support for Islamic organizations and religious leadership (ulama/kiai) played a significant role in mobilizing voters, explicit religious identity in candidates and promises to implement Sharia law were less effective. The research also highlights the complexities of identity politics in Madura, where the influence of local religious leaders and organizations often supersedes the broader national political narratives. These findings contribute to the broader discourse on identity politics in Indonesia and its implications for democratic stability.

IDEA AND PERSONA REPRESENTATION OF THE 2024 INDONESIA PRESIDENTIAL CANDIDATES: A SYSTEMIC FUNCTIONAL LINGUISTICS CASE STUDY

To achieve an ideal democratic process, voters need to have sufficient information about every candidate before making a well-informed decision. To understand the candidates’ values, one can look at their particular language choice which is realized in their idea representations from text elements (vision and mission statement) and persona representations from visual elements (campaign posters). Combining two theoretical frameworks, Systemic Functional Linguistics and The Grammar of Visual Design, this research aims to explain how presidential and vice presidential represent their ideas and personas through vision and mission and campaign posters in the 2024 Indonesia Presidential Election. Finding shows SFL and Visual Design Grammar can explain how politicians reflect their thought and ideas into set of material and mental clauses while supporting the clauses with respective posters, as shown by Candidate 1 and Candidate who enhance their ideas with a coherence visual elaboration, meanwhile Candidate 3 do not show idea and persona congruity in their texts and image representations

Market Reaction to the 2024 Election Results: Prabowo-Gibran's Presidential Announcement

This study examines the capital market's reaction to the announcement of Prabowo-Gibran’s victory in the 2024 Indonesian presidential election by the General Elections Commission (KPU) using event study methodology. The research focuses on abnormal returns, trading volume activity (TVA), and security return variability (SRV) of companies listed in the LQ-45 index. Data was collected for an event window spanning five days before and after the announcement. The results show no significant changes in abnormal returns, indicating that the market had already priced in the expected outcome prior to the official announcement. Trading volume activity increased slightly but this change was also not statistically significant,suggesting that the announcement did not introduce substantial new information. Similarly, SRV decreased slightly but not significantly, pointing to a relatively stable market reaction. The findings align with the Efficient Market Hypothesis, suggesting that the market had already absorbed the election outcome based on early survey data. These results contrast with previous studies that identified significant market reactions to political events, highlighting the unique nature of investor behavior in this particular event.

Impact of Indonesia Presidential Election Quick Count on Political Connected Stock Volatility: An Event Study

This study assesses the impact of the 2024 Indonesia Presidential Election quick count results on the stock volatility of politically connected firms listed on the Indonesia Stock Exchange. An event study methodology is employed, analyzing four politically affiliated companies—PMMP, TOBA, BRMS, and WIRG—across a six-day event window (T-3 to T+3). A market-adjusted return model calculated abnormal returns (AR) and cumulative abnormal returns (CAAR). The findings reveal a significant market reaction before the event, particularly on T-2, where the average abnormal return (AAR) peaked at 5.82%, mainly driven by PMMP’s strong return of 16.66%. However, the AAR fell sharply to -3.91% on T+3, indicating a market correction. The cumulative abnormal return (CAAR) reached a high of 6.63% on T-2 before declining to 1.48% on T+3. A T-test yielded a p-value of 0.092 at a 10% significance level, showing a statistically weak significance in pre-and post-event returns. While the quick count results impacted stock performance, the market reaction was moderate. This study provides valuable insights for investors, helping them understand the influence of political uncertainty on politically connected firms in emerging markets and make informed investment decisions.

Debunking disinformation on YouTube: a fact check on the 2024 Indonesian election

The increasing number of hoaxes circulating on digital platforms in Indonesia is concerning. Following the 2024 Indonesian presidential election, the spread of disinformation, specifically on YouTube, has intensified, posing significant risks to public trust and the electoral process. These hoaxes have the potential to destabilise societal harmony and influence voter perceptions. In response, fact-checker institutions have played a critical role in exposing disinformation. This article explores the mechanisms of assessing accuracy on YouTube during the 2024 election, focusing on how Indonesian fact-checking institutions operate. The research used a qualitative approach, with two data collection techniques– interviews with key stakeholders and field observations of fact-checking processes. This research revealed that fact-checking in Indonesia is falling behind the rapid disinformation production. Combating disinformation requires more than current efforts—it demands a coordinated, resource-intensive approach involving the executive, legislative, judiciary, and civil society's active engagement. Innovative policies, technological advancements, and well-trained human resources are imperative to ensure its effectiveness.

Sentiment Analysis For The 2024 Presidential Election (Pilpres) Using BERT CNN

The 2024 presidential election in Indonesia has generated tremendous enthusiasm on social media, particularly on the X platform. This research aims to analyze public sentiment regarding the 2024 presidential election by utilizing BERT and CNN methods. Sentiment analysis in the digital era is key to understanding the diverse social perspectives within society. The use of BERT, which has proven effective in understanding natural language context, and CNN, initially used for image analysis, will help in understanding public sentiment on X leading up to the 2024 presidential election. The research results show that the BERT model provides the best performance with an average accuracy of 90.02%, while CNN achieved 88.19%. The sentiment-based predictions using BERT for the three presidential candidates indicate that Prabowo Subianto is predicted to receive the highest support at 43.82%, followed by Ganjar Pranowo with 33.83%, and Anies Baswedan with 22.35%. A comparison of the prediction results with the actual election results shows that Prabowo Subianto was predicted to receive 43.82% of the vote, while the actual election results reached 58.58%, a difference of 14.76%. Ganjar Pranowo was predicted to receive 33.83% of the vote, while the actual results were 16.47%, with a difference of 17.36%. Anies Baswedan was predicted to receive 22.35% of the vote, with the actual result being 24.95%, a difference of 2.60%. This study indicates that the BERT model is effective in providing an accurate depiction of the 2024 Indonesian presidential election results.

Isu-Isu Politik dalam Kampanye Calon Presiden RI terhadap Preferensi Pemilih di Nusa Tenggara Barat

This study examines the preferences of voters in West Nusa Tenggara (NTB) in the context of the 2024 Indonesian presidential election and how various political issues influence their choices. Utilizing a quantitative approach and descriptive survey, data was collected from 2,672 respondents representing diverse educational and occupational backgrounds in the NTB region. The findings reveal various political issues affecting voter preferences, including economic, social, environmental, security, leadership, and other issues. The most dominant issue in NTB voters' preferences is Nationalist Religious Issues, with about 24% of respondents considering it the most important issue. Socialism and Cultural Issues also receive significant attention, reflecting concern for the preservation of local culture and social integration. Additionally, Education and Public Health Issues are high priorities for NTB voters, indicating the need for access to quality education and good healthcare services. This research provides a deeper understanding of the political dynamics in NTB and the factors influencing voter decisions. The results can guide presidential candidates and political parties in designing campaign platforms relevant to the needs of this region. Furthermore, this study can help enhance political participation, advance important issues, and strengthen political representation at the local level. Recommendations are given for further studies on the role of religion in NTB politics, evaluation of issue fulfillment in public policy, analysis of demographic changes, and studies on political participation in NTB. This research is expected to provide valuable contributions to understanding regional politics in Indonesia and voter preferences that could influence the outcome of the 2024 presidential election in NTB.

Exploring Sentiment Analysis for the Indonesian Presidential Election Through Online Reviews Using Multi-Label Classification with a Deep Learning Algorithm

Presidential elections are an important political event that often trigger intense debate. With more than 139 million users, YouTube serves as a significant platform for understanding public opinion through sentiment analysis. This study aimed to implement deep learning techniques for a multi-label sentiment analysis of comments on YouTube videos related to the 2024 Indonesian presidential election. Offering a fresh perspective compared to previous research that primarily employed traditional classification methods, this study classifies comments into eight emotional labels: anger, anticipation, disgust, joy, fear, sadness, surprise, and trust. By focusing on the emotional spectrum, this study provides a more nuanced understanding of public sentiment towards presidential candidates. The CRISP-DM method is applied, encompassing stages of business understanding, data understanding, data preparation, modeling, evaluation, and deployment, ensuring a systematic and comprehensive approach. This study employs a dataset comprising 32,000 comments, obtained via YouTube Data API, from the KPU and Najwa Shihab channels. The analysis is specifically centered on comments related to presidential candidate debates. Three deep learning models—Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (Bi-LSTM), and a hybrid model combining CNN and Bi-LSTM—are assessed using confusion matrix, Area Under the Curve (AUC), and Hamming loss metrics. The evaluation results demonstrate that the Bi-LSTM model achieved the highest accuracy with an AUC value of 0.91 and a Hamming loss of 0.08, indicating an excellent ability to classify sentiment with high precision and a low error rate. This innovative approach to multi-label sentiment analysis in the context of the 2024 Indonesian presidential election expands the insights into public sentiment towards candidates, offering valuable implications for political campaign strategies. Additionally, this research contributes to the fields of natural language processing and data mining by addressing the challenges associated with multi-label sentiment analysis.

Framing Gibran Rakabuming Raka: A Media Analysis of CNN Indonesia's Coverage of His Vice-Presidential Nomination

Indonesia will celebrate democracy in 2024. In order to nominate candidates for president and vice president of Indonesia between 2024 and 2029, a coalition of several political parties will be formed. Prabowo Subianto and his running mate, Gibran Rakabuming Raka, are among the presidential candidate pairings being promoted. However, because of his youth and PDI Perjuangan party connection, Gibrans's nomination as a vice presidential candidate generated a range of public reactions. The PDI Perjuangan has formally announced Ganjar Pranowo and Mahfud MD as their candidates for the next Indonesian presidential election. Other media channels, such as CNN Indonesia, have taken notice of Gibran's situation and have included large headlines and in-depth coverage on their websites. Gibran's coverage aims to clarify his role as Prabowo Subianto's running mate for vice president and as a member of the PDI Perjuangan party. The purpose of this study is to examine how Gibran's reputation was built within CNN Indonesia following his unsuccessful bid for vice president. The study used a case study approach and a descriptive qualitative methodology. The Zhongdang Pan and Gerald M. Kosicki framing analysis model, which identifies media with syntactic, script, thematic, and rhetorical structures, was used to analyze the CNN Indonesia media. According to the statistics, CNN Indonesia developed Gibran's viewpoint by taking into account a variety of viewpoints from other people. None of the four news stories that were examined contained a resignation letter explaining Gibran's reason for leaving the PDI Perjuangan cadre.

Live Streaming, Personal Branding and Political Communication: Gen Z's Active Participation in the 2024 Indonesian presidential election

Live Streaming, Personal Branding and Political Communication: Gen Z's Active Participation in the 2024 Indonesian presidential election

Sentiment Analysis of Social Media X in the 2024 Indonesian Presidential Election Using the Naive Bayes Algorithm: Candidates' Backgrounds and Political Promises

In 2024, Indonesia holds a presidential election, and the candidates are making promises to each other to attract voters. Many people gave their opinions on X. This study uses the Naïve Bayes algorithm to analyze the sentiment of these tweets, with the aim of understanding the background of the candidates and their campaign promises. Data is collected from X by crawling technique, then data is pre-processed, trained using Naïve Bayes model, and evaluated for accuracy. Sentiments in tweets were classified as positive, negative, or neutral. The results showed that the Prabowo Subianto - Gibran Rakabuming Raka pair was the most talked about with 1005 tweets, followed by Anis Rasyid Baswedan - Muhaimin Iskandar with 707 tweets, and Ganjar Pranowo - Mohammad Mahfud M.D. with 572 tweets. The Prabowo Subianto - Gibran Rakabuming Raka pair received the most positive sentiment, which was 446 more than the other candidates.

Third Time's the Charm:The Youth Vote and Prabowo's Victory in the 2024 Indonesian Presidential Election

After previous failed attempts, Prabowo Subianto won the 2024 Indonesian presidential election. In this article, we outline the events that unfolded in the run-up to the election before analyzing the drivers of Indonesian voting behaviour based on original survey data. Our analyses underscore the importance of transformations in the generational composition of the Indonesian electorate: younger voters, especially those born after the return of democracy, are fuelling its erosion with their support of a former general accused of human rights abuses. In addition to benefitting from the support of incumbent President Joko Widodo, we argue that Prabowo's victory was underpinned by a sophisticated social media campaign, the waning memory of Indonesia's authoritarian past, and a young populace anxious about their economic prospects.

The Appropriation of Religiousity in the 2024 Indonesian Presidential

Religious appropriation is a phenomenon that is continually reproduced in every electoral contestation. However, this context has not been discussed comprehensively in previous studies. In addition to responding to the shortcomings of previous studies, this study also focuses on explaining the characteristics, factors, and latent dangers of religious appropriation that occured in the 2024 Indonesian presidential election. This study reveals three important findings regarding the religious appropriation in the 2024 Indonesian presidential election. First, religious appropriation frequently manifests in the context of doctrine, language, and religious behaviors expressed outside the values and norms of religion. Second, cultural, spiritual, and structural factors have dominantly influenced the occurance of religious appropriation in the 2024 Indonesian presidential election. Third, the latent dangers of religious appropriation in the 2024 Indonesian presidential election often leads to intolerance, polarization, and persecution against religious communities even after the 2024 Indonesian presidential election. This study also recommends the importance of further studies that explain the attitudes of both formal and informal authorities in responding to religious appropriation in political contestation by conducting intensive interviews.

Twitter Sentiment Analysis Towards Candidates of the 2024 Indonesian Presidential Election

Long before the elections were held, the topic related to elections was widely discussed on news portals and social media, including Twitter. A few studies related to the Indonesian election have tried to predict candidates who will run for the presidential election, but there has been no research that examines public sentiment on social media towards each of the potential candidates. The main objective of this study is to analyze the public sentiment in Twitter towards potential candidates for the 2024 Indonesian presidential election. This research seeks to fill the gaps in previous research and become a reference for further research regarding sentiment analysis for election prediction using Twitter. The presidential candidates used in the research are the top 3 candidates based on the Poltracking survey, namely Ganjar Pranowo, Prabowo Subianto, and Anies Baswedan. The data were taken from January until October 2022, more than a year before the general election began. To predict the sentiment, four different machine-learning methods were used and compared to each other. There are Naïve Bayes, Support Vector Machines, Random Forests, and Neural Networks. Based on the sentiment results of each candidate, the highest sentiment towards Prabowo is neutral (55.49%), the highest sentiment towards Ganjar is positive (61.34%), and the highest sentiment towards Anies is neutral (44.84%). Results from the study also show that Anies was the presidential candidate who received more negative sentiment than the other two (56.63%). Meanwhile, Ganjar Pranowo got the most positive sentiment of all (42,69%). For the neutral sentiment, Anies Baswedan also got the most results (39,87%), followed by Prabowo (38.99%) and Ganjar Pranowo (21.14%). The result of the study also discovered that random forest and neural networks have the best performance for sentiment analysis.

Uncovering the Reasons Behind Abstain Voters' Stances in the 2024 Indonesian Presidential Election: Social Media X Study Cases

The Indonesian Government expects the participation of all Indonesian people in holding General Elections. However, according to the 2019 Political Statistics by BPS, there were 34.75 million people who did not exercise their right to vote or were abstain voters (golput) in the 2019 Election. This research aims to analyze individual attitudes towards abstaining voters using stance analysis and topic modelling. From 9,045 collected tweets, subsequent manual annotation revealed 2,566 pro stances, 5,264 neutral stances, and 1,215 contra stances. The classification models utilized are Random Forest, Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbor, and Gradient Boosting. The classification outcomes will be analyzed by comparing the accuracy, precision, recall, and F1-score results based on their algorithms and n-grams. The results obtained from the stance analysis show that Random Forest achieved the highest accuracy and precision scores, with values of 84% and 83%, respectively. The discussion topic among those supporting golput due to low trust in the presidential and vice-presidential candidates. Other topics mentioned public feels dissatisfied with the pairs of candidates.

Investigating visual engagement of Generation Z with presidential campaign infographics through Eye-Tracking technology

This study was designed to investigate the visual engagement of Generation Z with Indonesian presidential election campaign infographics utilizing eye-tracking technology. Notably, Generation Z forms a significant segment of first-time voters in the 2024 General Election and plays an integral role in political decision-making processes. Despite their pivotal role, a marked disengagement with political activities among this demographic presents significant challenges. Prior research has demonstrated that visual attention is modulated by experiential factors and personal biases. Consequently, this investigation seeks to elucidate the impact of infographics on the visual attention of participants with pre-established preferences for presidential candidates. Employing eye-tracking technology facilitated an objective assessment of the participants' subconscious reactions to the infographics. This study analyzed the distribution of visual attention across six defined Regions of Interest (ROI) among 60 participants. The findings reveal that 50% of the participants directed their gaze predominantly at the names of the candidate pairs, 27% at the image of the presidential candidate, 15% at quotes, 5% at the image of the vice-presidential candidate, 2% at the candidate number, and 1% at the vision statement. Additionally, it was observed that 55% of the participants consistently fixated on the infographics that corresponded to their preferred candidate pair from the onset to the conclusion of the recording, while 45% demonstrated variability in their viewing patterns. These insights afford valuable implications for political strategists aiming to forge more effective communication strategies with Generation Z, thereby enhancing their engagement in the political discourse, particularly in the context of general elections.

Political Buzzers’ Role on Social Media During The 2019 Indonesian Presidential Election

The 2019 presidential election involved political buzzers as one of the keys to the campaign on social media for both parties. The existence of the buzzers itself has a positive and negative impact on Indonesian society. Currently, the term “buzzers” have changed from a marketing function to a word that has a negative connotation because it is often identified with hoax news. This research uses qualitative methods, using literature studies from various documents, news, journals and previous research that are relevant to the role of buzzers in the spread of fake news on social media in the 2019 Presidential Election. After conducting searches and obtaining material that is relevant to the topic of analysis, this article analysed material and news developing in society regarding the role of buzzers in spreading hoaxes in the 2019 Presidential Election. The aim of the hoax campaign is to change the stigma from bad to good to increase electability and popularity, but it can also be the opposite, from good to bad. The 2019 presidential election noted that both parties were using them and at the same time were under attack from buzzers. One of the strategies used by buzzers during the 2019 Presidential Election is to normalise lies where both parties slander each other. The existence of a hoax campaign makes news about the Presidential Election confusing and needs to be checked carefully to ensure the facts of the news. Keywords: Election, Buzzer, social media, presidential election, fake news.