ResuMe is a web-based application developed as a final project for the Certified Internship and Independent Study Program (MSIB) "Artificial Intelligence 4 Jobs" at Orbit Future Academy. This application utilizes the Naïve Bayes algorithm to classify resumes into specific divisions, assisting Human Resources (HR) teams in the candidate selection process.
- Develop practical skills in the field of Artificial Intelligence (AI).
- Implement a resume classification model using an AI-based approach.
- Improve efficiency and accuracy in the candidate selection process.
- Python: The primary programming language.
- Flask: A web framework for building the application.
- Naïve Bayes: The main algorithm for resume classification.
- NLTK: For text preprocessing.
- TF-IDF: For text feature extraction.
- Ngrok: For public network access.
- Resume Upload: Users can upload resumes in PDF format.
- Automatic Classification: Resumes are categorized into six divisions:
- Business Development
- Digital Media
- Engineering
- Human Resource
- Sales
- Model Evaluation: Using Confusion Matrix, Precision, Recall, and F1-Score.
- Web-Based Interface: A user-friendly interface built with Flask.
- Clone Repository
git clone https://github.com/username/resume-classification.git cd resume-classification - Install Dependencies
pip install -r requirements.txt
- Run the Application
python app.py
- Use Ngrok for Public Access
ngrok http 5000
- Access the Application Open a browser and visit http://127.0.0.1:5000 or use the URL provided by Ngrok.
The dataset used is sourced from Kaggle, consisting of 677 entries across six resume categories.
- Model Accuracy: 83%
- Confusion Matrix: Used to assess classification performance.
- Evaluation Metrics: Precision, Recall, and F1-Score.
Ahmad Muyaqi Universitas Negeri Semarang
For any inquiries or suggestions, feel free to contact LinkedIn: https://www.linkedin.com/in/ahmadmuyaqi/.