Indonesian presidential election sentiment: Dataset of response public before 2024

Firdaus, Asno Azzawagama; Yudhana, Anton; Riadi, Imam; Mahsun,

doi:10.1016/j.dib.2023.109993

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…Using SEM PLS analysis, this study found varying effects of different political factors on voting decisions, with political trust playing a significant moderating role [12]. [14]; this study proposes a new approach to post-election auditing using untrusted scanners. The rescan audit workflow involves scanning, shuffling, and rescanning, with manual inspection of only a few ballots.…”

Section: Introductionmentioning

confidence: 93%

“…The rescan audit workflow involves scanning, shuffling, and rescanning, with manual inspection of only a few ballots. This protocol improves audit efficiency by incorporating automatic consistency checks, especially for strict selection [14]. This approach provides accuracy results 0.90 on the optimal feature subset resulting from the incremental feature selection method [20].…”

Section: Introductionmentioning

confidence: 99%

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Optimizing the 2024 Governor Election Quick Count with Extreme Gradient Boosting (XGBoost) to Increase Voting Prediction Accuracy

Suacana,

Suhariyanto,

Nuru

2024

ijsecs

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This research aims to increase the accuracy of vote predictions in the Quick Count process in the 2024 Governor Election using the XGBoost algorithm. Quick Count is a fast method for obtaining estimates of election results based on some of the data that has been calculated. The XGBoost algorithm was chosen because it has proven effective in various applications, including predictive modeling. This research analyzes the implementation of the XGBoost algorithm in modeling vote predictions for Quick Count, especially in the context of the 2024 gubernatorial election. By using various evaluation metrics such as accuracy, precision, recall, and F1-score, this research provides a comprehensive understanding of the performance of the XGBoost model. The research results show that the XGBoost algorithm achieves high accuracy, precision, recall, and F1 score, demonstrating its ability to classify sounds accurately. The practical implications of this research are significant in improving the integrity of the democratic process by providing more reliable and transparent election results. Additionally, this research paves the way for developing more sophisticated Quick Count methods by leveraging insights from previous research on machine learning techniques and data security.

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Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Optimizing the 2024 Governor Election Quick Count with Extreme Gradient Boosting (XGBoost) to Increase Voting Prediction Accuracy

Suacana,

Suhariyanto,

Nuru

2024

ijsecs

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“…Kembalinya ke sistem proporsional terbuka diharapkan dapat meningkatkan akuntabilitas caleg kepada pemilih. https://journal.pubmedia.id/index.php/lawjustice Selain itu, MK juga mengeluarkan putusan-putusan penting lainnya terkait dengan pemilu, seperti sistem verifikasi partai politik, ambang batas parlemen, dan dana kampanye (Firdaus, 2024). Putusan-putusan ini perlu dipahami dan dikaji secara mendalam untuk melihat implikasinya terhadap penyelenggaraan Pemilu 2024.…”

Section: Analisis Perubahan Putusan Mahkamah Konstitusi Dalam Konteks...unclassified

Analisis Perubahan Putusan Mahkamah Konstitusi dalam Konteks Pemilu 2024 Melalui Tinjauan Hukum Tata Negara

Paradita,

Triadi

2024

ijlj

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Artikel ini bertujuan untuk menganalisis perubahan putusan Mahkamah Konstitusi (MK) dalam konteks pemilihan umum (pemilu) tahun 2024 dengan menggunakan pendekatan hukum tata negara. Keputusan-keputusan MK memiliki peran krusial dalam menentukan validitas pemilu dan melindungi prinsip-prinsip demokrasi yang mendasarinya. Artikel ini menggunakan metode penelitian yuridis normatif dengan pendekatan studi pustaka. Artikel ini melakukan tinjauan terhadap putusan-putusan MK dalam pemilu sebelumnya dan membandingkannya dengan konteks pemilu tahun 2024. Dalam analisis ini, faktor-faktor yang mempengaruhi perubahan putusan MK akan diperhatikan, seperti perkembangan hukum, perubahan sosial, dan pergeseran politik yang mungkin terjadi seiring berjalannya waktu. Melalui tinjauan hukum tata negara, artikel ini juga akan mempertimbangkan pengaruh pemikiran konstitusionalis dan prinsip-prinsip hak asasi manusia dalam putusan MK terkait pemilu. Penelitian ini memperhatikan perubahan dalam interpretasi konstitusi oleh MK dan dampaknya terhadap proses pemilu. Hasil analisis ini diharapkan dapat memberikan pemahaman yang lebih baik tentang perubahan putusan MK dalam konteks pemilu 2024 dan implikasinya terhadap sistem demokrasi. Dengan memahami perubahan tersebut, para pemangku kepentingan dapat mengantisipasi dan merespons dengan tepat, yang pada gilirannya dapat meningkatkan integritas pemilu dan kepercayaan publik dalam proses demokrasi.

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“…-Manual labeling can consider text context when labeling, such as topic, author, and audience. Therefore, manual labeling is proposed as a validation technique due to its accuracy [49] compared to other labeling techniques using machine learning. Additionally, validation using manual labeling can build trust and improve model performance in machine-based labeling techniques.…”

Section: Data Preprocessing and Labellingmentioning

confidence: 99%

Sentiment Analysis on Marketplace in Indonesia using Support Vector Machine and Naïve Bayes Method

Dakwah,

Firdaus,

Furizal

et al. 2024

J. Ilm. Tek. Elektro Komput. Dan Inform

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This research addresses the challenges of marketplace customer feedback, which is an important aspect in today's era of online transactions. Marketplaces often receive many unsatisfactory comments from their customers through social media platforms. One approach that can be used to address this is sentiment analysis. This research contributes new insights as recommendations for marketplaces based on customer opinions on available services and delivery. The sentiment analysis methods used are Naive Bayes and Support Vector Machine because they are considered the best methods in training text-based classification models. Before being classified, the data goes through preprocessing stages such as cleaning, case folding, filtering, stemming, and tokenizing, as well as feature extraction stages using Term Frequency -Inverse Document Frequency (TF-IDF). The objects analyzed are divided into several well-known marketplaces in Indonesia such as Tokopedia, Lazada, and Shopee in discussing services and delivery of goods. The data used in this study comes from Twitter (X) social media accessed on August 27, 2023, using crawling techniques and successfully obtained as much as 2057 Tweet data. The best accuracy is obtained in the SVM method when compared to the Naive Bayes method. Words obtained based on service talks include price, service, application service, feedback, independence, and others. As for the delivery of goods, common words such as COD, delivery, package, courier, cheap, price, and others appear. Both methods used have good accuracy and can be recommended for use in similar research.

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Indonesian presidential election sentiment: Dataset of response public before 2024

Cited by 5 publications

References 13 publications

Optimizing the 2024 Governor Election Quick Count with Extreme Gradient Boosting (XGBoost) to Increase Voting Prediction Accuracy

Optimizing the 2024 Governor Election Quick Count with Extreme Gradient Boosting (XGBoost) to Increase Voting Prediction Accuracy

Analisis Perubahan Putusan Mahkamah Konstitusi dalam Konteks Pemilu 2024 Melalui Tinjauan Hukum Tata Negara

Sentiment Analysis on Marketplace in Indonesia using Support Vector Machine and Naïve Bayes Method

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