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Applying SVM and Random Forest Algorithms to Detect Hoax News at PT Global Arrow

An undergraduate hoax-news classification project using approximately 1,985 prepared Indonesian news records. The workflow retrieved document data from MongoDB and used JSON, CSV, and Excel working files before combining text mining and TF-IDF features with SVM and Random Forest models. A Figma concept guided the simple Streamlit interface. The repository is publicly archived as a research record.

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Applying SVM and Random Forest Algorithms to Detect Hoax News at PT Global Arrow

Applying SVM and Random Forest Algorithms to Detect Hoax News at PT Global Arrow

THE PROJECT

Project details

Started
January 2024

Built with

  • Python
  • TF-IDF
  • SVM
  • Random Forest
  • Text Mining
  • Machine Learning
  • Streamlit
  • MongoDB
  • JSON
  • CSV
  • Excel
  • Figma
  • Git

COLLABORATION

Built together.

Public credits for people who helped shape this project.

Rizky Tahara Shita

Research Supervisor · Co-author

Publication