Ar Rahmah, Zarah (2024) RANCANG BANGUN SISTEM INFORMASI CRM GUNA MENINGKATKAN SEGMENTASI PELANGGAN MENGGUNAKAN ALGORITMA K-NN BERBASIS WEB PADA KIM BEAUTY HOUSE. S1 / D3 thesis, Universitas Kuningan.

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Official URL: https://rama.uniku.ac.id

Abstract

Kim Beauty House Kuningan adalah klinik kecantikan dengan menawarkan solusi permasalahan kulit wajah dan kecantikan. Faktor yang perlu diperhatikan oleh sebuah perusahaan yaitu perusahaan menyadari target pasar yang dituju, dengan bagaimana melayani pelanggan untuk meningkatkan value sehingga perusahaan dapat mempertahankan loyalitas pelanggan terhadap pelanggan. Salah satu strategi yang dapat digunakan yaitu dengan menerapkan strategi Customer Relationship Management (CRM). Penelitian ini bertujuan untuk menganalisa pelanggan dengan sistem informasi Customer Relationship Management (CRM) berdasarkan RFM yang menggunakan metode k-Nearest Neighbors (KNN) dalam proses menganalisa pelanggan yang berpotensi dan tidak berpotensi. KNN merupakan metode untuk melakukan klasifikasi terhadap objek berdasarkan data pembelajaran yang jaraknya paling dekat dengan objek. Hasil menunjukan bahwa metode KNN mampu menganalisis pelanggan yang berpotensi sebesar 83,33% dan penggunaan parameter k mempengaruhi hasil klasifikasi. Berdasarkan hasil tersebut maka dapat memberikan referensi bagi perusahaan untuk membuat strategi penjualan.
Kata Kunci : Sistem Informasi, CRM, Segmentasi, RFM, K-NN.

Kim Beauty House Kuningan is a beauty clinic that offers solutions to facial skin and beauty problems. Factors that a company needs to pay attention to are that the company is aware of its target market, and how to serve customers to increase its value so that companies can maintain customer loyalty towards customers. One strategy that can be used to implement is Customer Relationship Management (CRM). This research aims to analyze customers with information systems Customer Relationship Management (CRM) based on RFM which uses the method k-Nearest Neighbors (KNN) in the process of analyzing potential and non-potential customers. KNN is a method for classifying objects based on learning data that is closest to the object. The results show that the KNN method is able to analyze 83.33% of potential customers and the use of parameters k affect the classification results. Based on these results, it can provide a reference for companies to create sales strategies.
Keywords : Information system, CRM, Segmentation, RFM, K-NN.

Item Type: Thesis (S1 / D3)
Uncontrolled Keywords: Sistem Informasi, CRM, Segmentasi, RFM, K-NN Information system, CRM, Segmentation, RFM, K-NN.
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > S1 Sistem Informasi
Depositing User: S. Kom Zarah Ar Rahmah
Date Deposited: 08 Oct 2024 04:32
Last Modified: 08 Oct 2024 04:32
URI: https://rama.uniku.ac.id/id/eprint/1376

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