Segmentasi Pelanggan Bisnis Kursus Berbasis LRFM Menggunakan t-SNE, UMAP, dan PaCMAP untuk Optimalisasi Profitabilitas Bisnis

Authors

  • Yanuar Rafi Rahadian Universitas Pembangunan Nasional "Veteran" Jawa Timur, Surabaya, Indonesia
  • Hasan Bisri Universitas Pembangunan Nasional "Veteran" Jawa Timur, Surabaya, Indonesia
  • Latifa Indirani Amina Universitas Pembangunan Nasional "Veteran" Jawa Timur, Surabaya, Indonesia

DOI:

https://doi.org/10.62411/tc.v24i3.13782

Abstract

Segmentasi pelanggan memainkan peran penting dalam meningkatkan profitabilitas bisnis dengan mengidentifikasi pola perilaku pelanggan. Penelitian ini mengusulkan pendekatan segmentasi berbasis model LRFM (Length, Recency, Frequency, Monetary) untuk meningkatkan ketepatan klasifikasi pelanggan. Dengan menggunakan data transaksi, skor LRFM dihitung dan diklasifikasikan ke dalam empat kategori: Best Customers (121 pelanggan), Loyal Customers, Potential, dan At Risk. Untuk meningkatkan interpretabilitas hasil, tiga teknik reduksi dimensi : t-SNE, UMAP, dan PaCMAP digunakan dalam analisis visual. Di antara ketiganya, UMAP menunjukkan visualisasi paling seimbang berdasarkan indikator separation clarity, cluster compactness, dan outlier identification. Hasil penelitian menunjukkan bahwa segmentasi visual membantu pengambil keputusan dalam mengidentifikasi kelompok pelanggan strategis untuk program retensi dan optimalisasi. Studi ini memberikan referensi berharga bagi industri yang ingin meningkatkan manajemen hubungan pelanggan melalui pendekatan berbasis data.   Kata kunci - Model LRFM, profitabilitas bisnis, reduksi dimensi, segmentasi pelanggan, UMAP

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Published

2025-08-18

Issue

Vol. 24 No. 3 (2025): Agustus 2025

Section

Articles

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Copyright (c) 2025 Yanuar Rafi Rahadian, Hasan Bisri, Latifa Indirani Amina

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