Work

A customer churn prediction using pearson correlation function and k nearest neighbor algorithm for telecommunication industry

Year: 2019

Type: article

Abstract: Customer churn in telecommunication industry is actually a \nserious issue. The Telco company needs to have a churn prediction model to prevent their customer from moving to another telco. Therefore, the objective of this paper is to propose the customer churn prediction using Pearson Correlation and K Nearest Neighbor algorithm. The algorithm is validated via training and testing dataset with the ratio 70:30. Based on experiment, the result shows that the K \nNearest Neighbor algorithm performs well compared to the others with the accuracy for training is 80.45% and testing 97.78%.

Source: UMP Institutional Repository (Universiti Malaysia Pahang)

Authors: Nilam Nur Amir Sjarif, M. R. M. Yusof, Doris Hooi-Ten Wong, Shamshul Bahar Yaakob, Rabha W. Ibrahim, Mohd Zamri Osman

Language: English

Topic: Customer churn and segmentation

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: green

Funder: Universiti Teknologi Malaysia

OpenAlex ID: W3132726656

FWCI: 3.609

Cites: 20

Cited by: 22

Related to: 10