Undergraduate Informatics student focused on Data Science, Applied Machine Learning, and Business Analytics. My background in SIJA (a vocational program in Information Systems, Networks, and Applications) gives me a practical foundation in databases, Linux servers, and cloud basics for working with data end to end.
- Machine Learning: Supervised and unsupervised modeling with Scikit-Learn on tabular data (clustering, classification, regression) and image features (OpenCV).
- Analytics & BI: Exploratory data analysis, KPI reporting, and interactive dashboards with Streamlit and Google Looker Studio.
- Technical Foundation: SQL and relational databases, Linux server administration, data pipelines, and AWS cloud basics, from vocational training.
Python (Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn) | SQL | Streamlit | Looker Studio | OpenCV | Linux | AWS
- Brazilian E-Commerce Performance Analysis: End-to-end analysis of 96K Olist orders covering category revenue, the effect of late deliveries on review scores, and customer geospatial mapping, delivered as an interactive Streamlit dashboard.
- Indonesia Supermarket Analytics: Retail data pipeline analyzing Indonesian supermarket transactions (2014-2017) with Looker Studio dashboards and predictive regression modeling.
- Bank Transaction Segmentation: Two-stage ML pipeline on 1,945 bank transactions: K-Means clustering followed by Decision Tree and Random Forest classification of the clusters, including an analysis of what drives the clusters.
- Celestial Object Classification: Image classification of 11 planets and moons using OpenCV features (intensity and edge histograms), comparing Decision Tree, SVM, and Logistic Regression in Scikit-Learn.