Kelvin, Kelvin (2022) Implementasi metode density based spatial clustering algorithm with noise untuk menentukan loyalitas pelanggan pada CV. SJSS. Bachelor thesis, Universitas Pelita Harapan.
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Abstract
Customer loyalty is very important for a business, both large and small businesses. CV. SJSS is a company in Medan which operates in the installation and sale of various types of CCTV camera products and accessories as well as other security devices, such as attendance machines, doorstops and so on. Currently, CV. SJSS use a desktop application to record its transaction data. However, the owner of CV. SJSS was unable to obtain information regarding the level of satisfaction and loyalty from the company's customers. To determine the level of customer loyalty, the analysis process can be carried out on sales data in the company. One
of the clustering methods that can be used is the Density Based Spatial Clustering Algorithm with Noise method. Conceptually, DBSCAN can form clusters that are free and random (not round) and can make it easier to form clusters if there is noise or outliers in these clusters. Based on the results of the tests carried out, information was obtained that the accuracy for the data tested from the Density Based Spatial Clustering Algorithm with Noise method was about 82.857%, so it could be used to analyze customer loyalty to the company./ Loyalitas pelanggan merupakan hal yang sangat penting bagi suatu bisnis, baik bisnis berskala besar maupun kecil. CV. SJSS adalah salah satu perusahaan
swasta di Medan yang bergerak di bidang pemasangan dan penjualan berbagai jenis produk dan aksesoris kamera CCTV serta perangkat keamanan lainnya, seperti mesin absensi, palang pintu dan sebagainya. Saat ini, CV. SJSS telah menggunakan sebuah aplikasi desktop dalam mencatat data transaksinya. Namun, pemilik CV.SJSS tidak dapat memperoleh informasi mengenai tingkat kepuasan dan loyalitas dari pelanggan perusahaan. Untuk mengetahui tingkat loyalitas pelanggan, maka dapat dilakukan proses analisis terhadap data penjualan di perusahaan. Salah satu metode clustering yang dapat digunakan adalah metode Density Based Spatial
Clustering Algorithm with Noise. Secara konsep DBSCAN dapat membentuk cluster-cluster yang berbentuk bebas dan acak (tidak bulat) dan dapat mempermudah membentuk cluster jika terdapat noise atau pencilan pada cluster-cluster tersebut. Berdasarkan hasil pengujian yang dilakukan, diperoleh informasi bahwa akurasi untuk data yang diuji dari metode Density Based Spatial Clustering Algorithm with Noise sekitar 82.857 %, sehingga hasil penelitian dapat digunakan
untuk menganalisis loyalitas pelanggan pada perusahaan.
Item Type: | Thesis (Bachelor) |
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Creators: | Creators NIM Email ORCID Kelvin, Kelvin NIM03082180014 kk80014@student.uph.edu UNSPECIFIED |
Contributors: | Contribution Contributors NIDN/NIDK Email Thesis advisor Ferawaty, Ferawaty NIDN0127047701 ferawaty.fik@uph.edu |
Uncontrolled Keywords: | customer loyalty; cluster; density based spatial clustering algorithm with noise; CV.SJSS |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | University Subject > Current > Faculty/School - UPH Medan > School of Information Science and Technology > Informatics Current > Faculty/School - UPH Medan > School of Information Science and Technology > Informatics |
Depositing User: | Users 24147 not found. |
Date Deposited: | 16 Aug 2022 06:12 |
Last Modified: | 25 Aug 2022 07:43 |
URI: | http://repository.uph.edu/id/eprint/49663 |