post – Daffa Daniel Rivaldi

Churn Prediction: 12-week Observation window with 1-Week Gap

Built a customer churn prediction model using RFM-T feature as predictors that is extracted from the past 12-week observation windows with a 1-week gap. Achieved realistic…

Customer Retention Cohort Analysis

Analyzing Customer Cohorts to Improve Retention & Value

Designing and Creating Relational Database for Doctor-Patient Appointments

In this post, I will design a simple database system for hospital app to manage patient medical records and doctor appointments using postgresql. Through this project, I…

Customer Segmentation using RFM Analysis and K-Means Clustering

Segmented xx customers into x actionable groups using RFM + K-Means, unlocking clear retention and re-engagement strategies.

Used Car Price Prediction

An end-to-end machine learning project to predict used car prices based on features like brand, model, year, mileage, fuel type, transmission, etc. Includes data cleaning…