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  • Jakarta, Indonesia

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danusetiawan05/README.md

Hi there!

I'm Danu - a fresh graduate with a growing passion for Data Science and Analytics. I enjoy working with data using Python (Pandas, NumPy) and SQL, from cleaning and exploring datasets to uncovering meaningful patterns. I'm still exploring different areas within data science to find where my interest fits best, and I'm always excited to learn new tools and take on real-world data projects. Open to collaboration and new opportunities!

  • 🔭 Currently exploring: Data Science - Data Analysis & Machine Learning fundamentals
  • 🌱 Learning: Data Analysis & Machine Learning fundamentals, especially SQL for data analysis and exploratory data analysis (EDA) techniques
  • 💬 Ask me about: Python, Pandas, NumPy, SQL
  • 📫 Open to: internship / entry-level Data Science or Data Analyst opportunities

🛠️ Tech Stacks

Python MySQL Laravel

📊 GitHub Statistics

🤝 Connect with me

LinkedIn Gmail

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  1. Classification-and-Regression-Gender-Empowerment-Index Classification-and-Regression-Gender-Empowerment-Index Public

    Classification (KNN) and regression (Linear Regression) analysis of Indonesia's Gender Empowerment Index (IDG) across regencies/cities (2021-2023), with leakage-free modeling and validated forecast…

    Jupyter Notebook

  2. Classification-Gym-Member-Exercise-Tracking Classification-Gym-Member-Exercise-Tracking Public

    Classifying gym members' experience level using Decision Tree, based on workout habits and physical attributes includes EDA, cross-validated modeling, and feature importance analysis.

    Jupyter Notebook

  3. Student-Performance-Classification-DT-vs-KNN Student-Performance-Classification-DT-vs-KNN Public

    Comparing Decision Tree and KNN to classify student pass/fail status based on academic performance factors, with EDA-driven feature selection and cross-validated tuning for both models.

    Jupyter Notebook

  4. Classification-of-Nutritional-Value-Levels-of-Food-and-Beverages Classification-of-Nutritional-Value-Levels-of-Food-and-Beverages Public

    Classifying food and beverage nutritional value levels (Low/Medium/High) using an Artificial Neural Network (ANN), with optimizer, activation, and learning rate experiments.

    Jupyter Notebook

  5. Chayote-Freshness-Clustering-Using-KMeans Chayote-Freshness-Clustering-Using-KMeans Public

    Clustering chayote freshness based on color and texture features extracted from images, using K-Means with objective cluster selection via Silhouette Score.

    Jupyter Notebook

  6. Classification-of-Customer-Satisfaction-Ratings-Based-on-Shopping-Patterns Classification-of-Customer-Satisfaction-Ratings-Based-on-Shopping-Patterns Public

    Classifying customer satisfaction levels (Low/Neutral/High) based on shopping patterns using Random Forest, with evaluation via baseline and cross-validation.

    Jupyter Notebook