UTS Pemrograman Sains Data

End‑to‑end comparison of Random Forest and Gradient Boosting classifiers on an imbalanced phishing‑email dataset. We split 60/20/20, applied down‑sampling, up‑sampling, ROSE and SMOTE, tuned probability thresholds to maximize F₁, then evaluated the champion model on a held‑out test set

Análise de aceitabilidade da desigualdade a partir do Latinobarômetro - Rodada 2023

DS2003 Final Project

Problems 3, 8, and 9

Retention analysis for PapayaPay explores user engagement, retention rates, churn dynamics, and key business opportunities uncovered from billing data through April 2025. The report highlights critical findings such as repeat usage patterns, time-to-repeat behavior, high-value customer segments, and payment channel efficiency, providing actionable insights to optimize user retention and enhance business strategies.