Implementation of Text Mining for Emotion Detection Using The Lexicon Method (Case Study: Tweets About Pemilu 2024)

Penulis

  • Afifah Salsabilah Putri Universitas Negeri Padang
  • Eujeniatul Jannah Departemen Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Padang, Indonesia
  • Dodi Vionanda Departemen Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Padang, Indonesia
  • Syafriandi Departemen Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Negeri Padang, Indonesia

DOI:

https://doi.org/10.24036/ujsds/vol3-iss1/348

Kata Kunci:

Emotion, Twitter, President election

Abstrak

The presidential election is a five-year event that is an important and crucial moment in the realisation of democracy in the Unitary State of the Republic of Indonesia (NKRI). In the modern political era, the development of information technology has had a significant impact in changing the way people interact and express their views on political issues, including in the Presidential election.  One of the social media platforms that is often used to debate political and social issues is Twitter. The analysis method used in this research is sentiment and emotion analysis with a lexicon-based approach. The research stages consist of twitter data collection, data preprocessing, and emotion feature extraction. The first word to be highlighted in the 2024 election series on twitter social media is Anies. Trust is the most dominant emotion towards the three candidate pairs, namely Anies Muhaimin, Prabowo Gibran, and Ganjar Mahfud, showing high public trust.

Diterbitkan

2025-02-28

Cara Mengutip

Afifah Salsabilah Putri, Eujeniatul Jannah, Dodi Vionanda, & Syafriandi. (2025). Implementation of Text Mining for Emotion Detection Using The Lexicon Method (Case Study: Tweets About Pemilu 2024). UNP Journal of Statistics and Data Science, 3(1), 100–107. https://doi.org/10.24036/ujsds/vol3-iss1/348

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