Aplikasi website klasifikasi piutang customer dengan metode k-means clustering pada PT. Sumber Sejahtera Raya

Michael, Michael (2021) Aplikasi website klasifikasi piutang customer dengan metode k-means clustering pada PT. Sumber Sejahtera Raya. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

PT. Sumber Sejahtera Raya adalah sebuah perusahaan yang menjual produk cat dan alat-alat untuk mengecat. Masalah yang terjadi di PT. Sumber Sejahtera Raya yaitu pihak manajemen perusahaan kesulitan melakukan pengelompokkan customer berdasarkan piutangnya. Hal ini mengakibatkan pihak manajemen perusahaan kesulitan memperoleh informasi mengenai kelompok customer yang menunggak atau yang membayar tepat waktu. Untuk menyelesaikan permasalahan tersebut, maka diterapkan metode klasifikasi K-Means Clustering. Hasil dari penelitian ini adalah sebuah website yang dapat digunakan untuk mengklasifikasikan customer berdasarkan kondisi piutangnya. Hasil klasifikasi customer ini dapat digunakan untuk mengetahui customer yang sering menunggak piutang dan customer yang sering membayar tepat waktu./PT. Sumber Sejahtera Raya is a company that sells paint products and tools for painting. Problems that occur in PT. Sumber Sejahtera Raya, namely the company's management has difficulty classifying customers based on their receivables. This has resulted in the company's management having difficulty obtaining information about groups of customers who are in arrears or who pay on time. To solve this problem, the K-Means Clustering classification method is applied. The result of this research is a website that can be used to classify customers based on the condition of their receivables. The results of this customer classification can be used to identify customers who are often in arrears and customers who often pay on time.
Item Type: Thesis (Bachelor)
Creators:
Creators
NIM
Email
ORCID
Michael, Michael
NIM03081170014
michaelyungsen@gmail.com
UNSPECIFIED
Contributors:
Contribution
Contributors
NIDN/NIDK
Email
Thesis advisor
Chandra, Wenripin
NIDN0116088001
wripin@gmail.com
Uncontrolled Keywords: klasifikasi customer; metode k-means clustering
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: University Subject > Current > Faculty/School - UPH Medan > School of Information Science and Technology > Information Systems
Current > Faculty/School - UPH Medan > School of Information Science and Technology > Information Systems
Depositing User: Users 18799 not found.
Date Deposited: 06 Aug 2021 05:48
Last Modified: 12 Jan 2022 09:04
URI: http://repository.uph.edu/id/eprint/41241

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