Segmentasi Customers Usaha Persewaan Alat Proyek Dengan Rfm Model Menggunakan K-Means Algorithm

Putri, Denurta Dimurtianti (2025) Segmentasi Customers Usaha Persewaan Alat Proyek Dengan Rfm Model Menggunakan K-Means Algorithm. Other thesis, Institut teknologi Sepuluh Nopember.

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Abstract

Bidang konstruksi terus mengalami kemajuan seiring dengan pesatnya pembangunan infrastruktur. Salah satu perkembangan signifikan dalam bidang konstruksi adalah peningkatan permintaan alat-alat proyek. Persewaan alat proyek seperti Persewaan Alat Proyek XYZ di Surabaya, merasakan dampak langsung dari peningkatan ini. Namun, perusahaan ini menghadapi tantangan dalam mengelompokkan customers karena variasi dalam karakteristik dan kebutuhan mereka. Penelitian ini bertujuan untuk mengidentifikasi dan mengelompokkan customers Persewaan Alat Proyek XYZ berdasarkan karakteristik transaksi mereka guna merekomendasikan strategi pemasaran yang lebih efektif. Penelitian ini menggunakan model RFM (Recency, Frequency, Monetary) untuk mengukur perilaku customers. Pembobotan atribut RFM dilakukan menggunakan metode AHP (Analytic Hierarchy Process) untuk menentukan bobot yang paling sesuai berdasarkan prioritas bisnis. Selanjutnya, algoritma K-Means digunakan untuk segmentasi customers, dengan jumlah cluster optimal ditentukan melalui metode Elbow. Hasil penelitian menunjukkan bahwa pelanggan terbagi menjadi tiga cluster berdasarkan karakteristik transaksi, yaitu Golden Customers, Occasional Customers, dan Superstar Customers, dengan masing-masing memiliki jumlah anggota 260, 131, dan 18.
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The construction sector continues to advance alongside the rapid development of infrastructure. One significant development in this field is the increasing demand for project equipment. Equipment rental services, such as XYZ Project Equipment Rental in Surabaya, have directly benefited from this growth. However, the company faces challenges in segmenting its customers due to variations in their characteristics and needs. This study aims to identify and segment the customers of XYZ Project Equipment Rental based on their transaction characteristics to recommend more effective marketing strategies. The study employs the RFM (Recency, Frequency, Monetary) model to analyze customers behavior. The weighting of RFM attributes is carried out using the AHP (Analytic Hierarchy Process) method to determine the most appropriate weights based on business priorities. Subsequently, customers segmentation is conducted using the K-Means algorithm, with the optimal number of clusters determined through the Elbow method. The results indicate that customers are divided into three clusters based on transaction characteristics: Golden Customers, Occasional Customers, and Superstar Customers, with 260, 131, and 18 members, respectively.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Analytic Hierarchy Process, Karakteristik customers, Clustering K-Means, Model RFM, Segmentasi customers, Analytic Hierarchy Process, Customers Characteristic, Geographic analysis, K-Means Clustering, RFM models
Subjects:	H Social Sciences > HB Economic Theory > HB801 Consumer behavior. H Social Sciences > HF Commerce > HF5415.127 Market segmentation. Target marketing H Social Sciences > HF Commerce > HF5415.15 Branding (Marketing) H Social Sciences > HF Commerce > HF5415.5 Customer services. Customer relations Q Science > QA Mathematics > QA76.9.D343 Data mining. Querying (Computer science)
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Denurta Dimurtianti Putri
Date Deposited:	05 Feb 2025 10:20
Last Modified:	05 Feb 2025 10:20
URI:	http://repository.its.ac.id/id/eprint/118311

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