Segmentasi Pelanggan Internet Service Provider (ISP) Berbasis Pillar K-Means customer segmentation, pillar K-Means, RFM
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Abstract
Perusahan penyedia layanan internet service provider (ISP) memiliki jumlah pelanggan yang sangat banyak dan beragam. Dengan semakin banyak dan beraamnya jumlah pelanggan peusahaan akan sulit untuk mengetahui tipe pelanggan yang dimiliki oleh perusahaan. Akibatnya perusahaan akan kesulitan menerapkan strategi pemasaran yang tepat kepada konsumen. Dalam paper ini digunakan metode pillar K-means untuk melakukan segmentasi pelanggan. Algoritma pilar k-means untuk melakukan segmentasi pelanggaran . Algoritma Pillar merupakan metode optimasi untuk menentukan centroid awal dalam algoritma K-Means. Dengan mengoptimasi centroid awal maka akan menghasilkan cluster yang lebih baik . setelah memperoleh hasil cluster yang optimal selanjutnya tipe pelanggaran dianalisis dengan menggunakan metode RFM (Recency, Frequency, Montetery). Hasil penelitian ini menunjukan bahwa pllar K-means mampu mengoptimasi hasil cluster : k = 4 dengan a = 0.5 dan b = 0.8 serta nilai silheoette 8 = 0.47103. Dari hasil segmentasi 150 pelangganan diperoleh tipe pelangganan yang terdiri Most Valuable Costmers (33) Most Growable Costomers (41), Migrators (23) dan Below Zero (53).
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