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Dio Rizkyandita
ID

Research

Turning transaction data into decisions

My Master's research in Information Technology focuses on machine learning for customer segmentation — grounded in the real problems of a growing B2B business.

Paper Published

CLV-Enhanced RFM Framework for Customer Segmentation in Indonesian SMEs Using K-Means Clustering

This study examines Recency, Frequency, Monetary (RFM) metrics and Customer Lifetime Value within the context of MSMEs in Indonesia, specifically in the city of Mataram. The research focuses on F&B businesses particularly coffee shops exploring how to capture customer value through segmentation and translate these insights into sound business decisions that ensure the sustainability of MSMEs.

Methods: RFM Analysis · K-Means · Silhouette Score · Cutomer Lifetime Value