Implementation of K-Nearest Neighbor Algorithm for Customer Satisfaction

  • Sutan Faisal Sutan Faisal Ubp Karawang
  • Nurhayati Sutan Faisal Universitas Buana Perjuangan Karawang
Keywords: Datamining, classification, KNN algorithm, customer satisfaction

Abstract

Customer satisfaction is one of the goals of the company in providing services to its customers both service and non-service companies. One of the camera rental service provider companies that are committed to customer satisfaction is Cikarang Camera Rental. This study aims to analyze customer satisfaction in Cikarang camera rental using the K Nearest Neighbor (KNN) algorithm. Customer satisfaction input attributes in this study include price, facilities, and dam loyalty services. The output results from the input attributes above are satisfied and not satisfied. This research is expected to help Cikarang Camera Rental to increase customer satisfaction and increase profit on Cikarang Camera Rental. The results of the research that can be achieved using the KNN algorithm are accuracy = 98%, classification recall = 86.67%, Classification precision = 100% and AUC = 0.750. The results of this study can be used as a reference to build an application that can facilitate companies in obtaining information about customer satisfaction.Keywords— Datamining, classification, KNN algorithm, customer satisfaction

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Published
2020-07-10
How to Cite
[1]
S. F. Sutan Faisal and N. Sutan Faisal, “Implementation of K-Nearest Neighbor Algorithm for Customer Satisfaction”, bit-cs, vol. 1, no. 2, pp. 27-32, Jul. 2020.