The Comparison of Random Forest and Artificial Neural Network for Customer Churn Prediction in Telecommunication-Reference-Cited by-同舟云学术

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The Comparison of Random Forest and Artificial Neural Network for Customer Churn Prediction in Telecommunication

Published:2023-12-06 Issue: Volume:9 Page:224-229
ISSN:
Container-title:2023 3rd International Conference on Smart Cities, Automation & Intelligent Computing Systems (ICON-SONICS)
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Author:

Ramadhan Aldandi Fitra¹,Permai Syarifah Diana¹,Harefa Jeklin²,Alexander ²

Affiliation:

1. Bina Nusantara University,School of Computer Science,Statistics Department,Jakarta,Indonesia,11480

2. Bina Nusantara University,School of Computer Science,Computer Science Department,Jakarta,Indonesia,11480

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10434938/10434948/10435087.pdf?arnumber=10435087

Reference28 articles.

1. Intelligent data analysis approaches to churn as a business problem: a survey

2. Comparison of Logistic Regression and XGBoost for Predicting Potential Debtors

3. Factors Influence Customer Churn on Internet Service Provider in Indonesia

4. A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector

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