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All Journal Techno.Com: Jurnal Teknologi Informasi InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Tekno Insentif
Rd. Nuraini Siti Fathonah
Politeknik Pos Indonesia
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : Jurnal Tekno Insentif

 1 
Penerapan Metode Algoritma K-Means untuk Menentukan Pemberian Reward terhadap Pelanggan PT. Telkom Kandatel Bone Muh. Rifky Prananda; Rd. Nuraini Siti Fathonah; Nisa Hanum Harani
Jurnal Tekno Insentif Vol 15 No 2 (2021): Jurnal Tekno Insentif
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah IV

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36787/jti.v15i2.570

Abstract

Abstrak Meningkatnya pertumbuhan industri menjadikan perusahaan bersaing mempertahankan pelanggannya. Persaingan di dunia industri memacu perusahaan untuk mencari cara agar penjualan meningkat disertai loyalitas pelanggannya. Pemberian reward merupakan salah satu piliha yang bisa dilakukan oleh perusahaan. Penelitian ini dirancang dengan menggunakan metode minmax dalam penyetaraan nilai atribut. Untuk proses clustering digunakan teknik pengelompokan k-means sebagai penentu pelanggan penerima reward. Sejumlah 10 sampel data pelanggan telah diujikan. Hasil dari metode algoritma k-means adalah 2 dari 10 pelanggan dinyatakan layak menerima reward, 4 pelanggan kurang layak mendapatkan reward, dan 4 pelanggan tidak layak mendapatkan reward. Hasil penelitian ini dapat membantu perusahaan dalam pemilihan pelanggan terbaik penerima reward dan diharapkan akan mampu meningkatkan loyalitas pelanggan. Abstract The increasing growth of the industry makes companies compete to retain their customers. Competition in the industrial world spurred companies to look for ways to increase sales with customer loyalty. Giving rewards is one of the choices that can be made by the company. This study was designed using the minmax value method in equalizing attributes. For the clustering process, the k-means grouping technique is used as a determinant of reward recipient customers. A total of 10 samples of customer data have been tested. The results of the k-means algorithm method are 2 out of 10 customers who are declared eligible to receive rewards, 4 customers are less deserving of rewards, and 4 customers are not eligible for rewards. The results of this study can help companies in selecting the best customers who receive rewards and is expected to increase customer loyalty.
Co-Authors Dyah Ayu Anandra Indra Riksa Herlambang Mohamad Nurkamal Fauzan Muh. Rifky Prananda Nisa Hanum Harani