A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry
Customer churn in telecommunication industry is actually a serious 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...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Soft Computing Research Group, UTM Malaysia
2019
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/25630/1/A%20Customer%20Churn%20Prediction%20using%20Pearson.pdf http://umpir.ump.edu.my/id/eprint/25630/ http://home.ijasca.com/data/documents/04_Page46-59_A-Customer-Churn-Prediction-using-Pearson.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Malaysia Pahang |
Language: | English |
id |
my.ump.umpir.25630 |
---|---|
record_format |
eprints |
spelling |
my.ump.umpir.256302019-08-14T03:52:02Z http://umpir.ump.edu.my/id/eprint/25630/ A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry Nilam Nur Amir, Sjarif Muhammad Rusydi, Mohd Yusof Doris Hooi, Ten Wong Suraya, Ya’akob Roslina, Ibrahim Mohd Zamri, Osman TK Electrical engineering. Electronics Nuclear engineering Customer churn in telecommunication industry is actually a serious 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 Nearest Neighbor algorithm performs well compared to the others with the accuracy for training is 80.45% and testing 97.78%. Soft Computing Research Group, UTM Malaysia 2019 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25630/1/A%20Customer%20Churn%20Prediction%20using%20Pearson.pdf Nilam Nur Amir, Sjarif and Muhammad Rusydi, Mohd Yusof and Doris Hooi, Ten Wong and Suraya, Ya’akob and Roslina, Ibrahim and Mohd Zamri, Osman (2019) A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry. International Journal of Advances in Soft Computing & Its Applications, 11 (2). pp. 46-59. ISSN 2074-8523 http://home.ijasca.com/data/documents/04_Page46-59_A-Customer-Churn-Prediction-using-Pearson.pdf |
institution |
Universiti Malaysia Pahang |
building |
UMP Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Pahang |
content_source |
UMP Institutional Repository |
url_provider |
http://umpir.ump.edu.my/ |
language |
English |
topic |
TK Electrical engineering. Electronics Nuclear engineering |
spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Nilam Nur Amir, Sjarif Muhammad Rusydi, Mohd Yusof Doris Hooi, Ten Wong Suraya, Ya’akob Roslina, Ibrahim Mohd Zamri, Osman A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry |
description |
Customer churn in telecommunication industry is actually a
serious 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
Nearest Neighbor algorithm performs well compared to the others with the accuracy for training is 80.45% and testing 97.78%. |
format |
Article |
author |
Nilam Nur Amir, Sjarif Muhammad Rusydi, Mohd Yusof Doris Hooi, Ten Wong Suraya, Ya’akob Roslina, Ibrahim Mohd Zamri, Osman |
author_facet |
Nilam Nur Amir, Sjarif Muhammad Rusydi, Mohd Yusof Doris Hooi, Ten Wong Suraya, Ya’akob Roslina, Ibrahim Mohd Zamri, Osman |
author_sort |
Nilam Nur Amir, Sjarif |
title |
A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry |
title_short |
A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry |
title_full |
A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry |
title_fullStr |
A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry |
title_full_unstemmed |
A Customer Churn Prediction using Pearson Correlation Function and K Nearest Neighbor Algorithm for Telecommunication Industry |
title_sort |
customer churn prediction using pearson correlation function and k nearest neighbor algorithm for telecommunication industry |
publisher |
Soft Computing Research Group, UTM Malaysia |
publishDate |
2019 |
url |
http://umpir.ump.edu.my/id/eprint/25630/1/A%20Customer%20Churn%20Prediction%20using%20Pearson.pdf http://umpir.ump.edu.my/id/eprint/25630/ http://home.ijasca.com/data/documents/04_Page46-59_A-Customer-Churn-Prediction-using-Pearson.pdf |
_version_ |
1643670049232257024 |