Sistem Rekomendasi Promosi dan Diskon Layanan Klinik Kecantikan Griya Ayu Queen's Berbasis Web
Keywords:
recommendation system, beauty clinic, promotion, discount, web application, analytical CRM, K-Means clustering, RFM, recommendation system, web-based systemAbstract
Abstrak
Klinik Kecantikan Griya Ayu Queen's menghadapi permasalahan dalam pengelolaan strategi promosi dan diskon layanan yang masih dilakukan secara manual dan tidak terarah. Hal ini menyebabkan rendahnya efektivitas promosi dan tingkat retensi pelanggan. Penelitian ini bertujuan merancang dan membangun Sistem Rekomendasi Promosi dan Diskon Layanan Klinik Kecantikan Griya Ayu Queen's Berbasis Web dengan menerapkan konsep Analytical Customer Relationship Management (CRM). Sistem ini mengintegrasikan analisis Recency, Frequency, Monetary (RFM) untuk merepresentasikan perilaku transaksi pelanggan dan algoritma K-Means clustering untuk mengelompokkan pelanggan berdasarkan kemiripan karakteristik transaksi. Hasil clustering digunakan sebagai dasar rekomendasi promosi dan diskon yang relevan bagi setiap segmen pelanggan. Pengujian sistem menggunakan metode Black Box Testing menunjukkan bahwa seluruh fungsionalitas sistem berjalan sesuai kebutuhan. Sistem yang dibangun mampu meningkatkan efektivitas promosi melalui segmentasi pelanggan berbasis data, mengurangi beban kerja administratif, serta mendukung pengiriman notifikasi promosi otomatis melalui integrasi WhatsApp Gateway. Dengan demikian, sistem ini memberikan solusi CRM analitik yang personal, terukur, dan proaktif untuk Klinik Kecantikan Griya Ayu Queen's.
Kata kunci: CRM analitik, K-Means clustering, RFM, sistem rekomendasi, web-based system
Abstract
Griya Ayu Queen's Beauty Clinic faces challenges in managing promotion and discount strategies that are still conducted manually and without proper direction, resulting in low promotion effectiveness and customer retention rates. This study aims to design and develop a Web-Based Promotion and Discount Recommendation System for Griya Ayu Queen's Beauty Clinic by implementing the concept of Analytical Customer Relationship Management (CRM). The system integrates Recency, Frequency, Monetary (RFM) analysis to represent customer transaction behavior and K-Means clustering algorithm to group customers based on transaction characteristic similarity. The clustering results serve as the basis for relevant promotion and discount recommendations for each customer segment. System testing using the Black Box Testing method shows that all system functionalities work as required. The developed system effectively enhances promotion effectiveness through data-driven customer segmentation, reduces administrative workload, and supports automated promotion notification delivery through WhatsApp Gateway integration. Thus, this system provides a personal, measurable, and proactive analytical CRM solution for Griya Ayu Queen's Beauty Clinic.
Keywords: analytical CRM, K-Means clustering, RFM, recommendation system, web-based system
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