JUDUL TA-Submit Jurnal Ekonomi dan Keuangan "Customer Segmentation and Classification Using RFM Model, K-Means, and Random Forest: A Case Study on Pizza Store X"

Alifiar, Muhamad Yusuf (2026) JUDUL TA-Submit Jurnal Ekonomi dan Keuangan "Customer Segmentation and Classification Using RFM Model, K-Means, and Random Forest: A Case Study on Pizza Store X". Bachelor thesis, Institut Teknologi Kalimantan.

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Abstract

The increasingly competitive fast-food industry requires companies to gain a deeper understanding of customer behavior in order to enhance customer retention and reduce the risk of customer churn. Store Pizza X, a culinary business operating in Balikpapan City, faces challenges in managing customer data optimally due to the absence of a structured data-driven customer analysis system. Therefore, this study aims to perform customer segmentation and predict customer segments based on transaction patterns.This study utilizes customer transaction data from Store Pizza X collected between July and October 2025. The Recency, Frequency, Monetary (RFM) method is applied to measure customer value based on transaction behavior, followed by customer segmentation using the K-Means clustering algorithm. Subsequently, the Random Forest algorithm is employed to develop a classification model for predicting customer segments. The quality of the clustering results is evaluated using the Silhouette Score, while the classification model performance is assessed using a Confusion Matrix, which produces accuracy, precision, and recall metrics.The results of this study are expected to provide clear customer segmentation and a stable, accurate prediction model. These findings are anticipated to deliver practical insights for Store Pizza X in developing data-driven marketing and customer retention strategies, as well as to serve as an academic reference for the application of RFM, K-Means, and Random Forest methods in the fast-food industry

Item Type: Thesis (Bachelor)
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: Jurusan Teknologi Industri dan Proses > Teknik Industri
Depositing User: Muhamad Yusuf Alifiar
Date Deposited: 15 Jul 2026 03:53
Last Modified: 15 Jul 2026 03:53
URI: http://repository.itk.ac.id/id/eprint/25959

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