Customer churn classification in telecommunication company using rough set theory

Churn is perceived as the behaviour of a customer to leave or to terminate a service. This behaviour causes the loss of profit to companies because acquiring new customer incurred high investment for advertisements and promotions compared to retaining existing ones. Thus, it is necessary to consider...

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Main Author:	Nur Syafiqah, Mohd Nafis
Format:	Thesis
Language:	English
Published:	2016
Subjects:	QA Mathematics
Online Access:	http://umpir.ump.edu.my/id/eprint/16930/1/Customer%20churn%20classification%20in%20telecommunication%20company%20using%20rough%20set%20theory.pdf
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id	my-ump-ir.16930
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spelling	my-ump-ir.169302023-05-30T07:54:42Z Customer churn classification in telecommunication company using rough set theory 2016 Nur Syafiqah, Mohd Nafis QA Mathematics QA75 Electronic computers. Computer science Churn is perceived as the behaviour of a customer to leave or to terminate a service. This behaviour causes the loss of profit to companies because acquiring new customer incurred high investment for advertisements and promotions compared to retaining existing ones. Thus, it is necessary to consider an efficient classification model to reduce the rate of churn. In the traditional approach of classification modelling, it do not produce straightforward result interpretation. Therefore, identifying the best classification model to reduce the rate of churn is indeed a challenging task. The main objective of this thesis is to propose a new classification model based on the Rough Set Theory to classify customer churn. This research utilized the Knowledge Discovery in Database (KDD) process involving data pre-processing, data discretization, attribute reduction, rule generation, classification process, as well as data analysis, using the Rough Set toolkit. The Rough Set theory elements consist of indiscernibility relation, lower and upper approximations, as well as reduction set. Those elements are applied to classify customer chum from uncertain and imprecise dataset. The results of the proposed model are compared with a few established existing approaches. The results of the study show that the proposed classification model outperformed the existing models and contributes to significant accuracy improvement. The model is tested using dataset form local telecommunication company which achieves 90.32%. In conclusion, the results proved that the classification model based on Rough Set Theory had been capable to classify customer chum compared to the existing model. 2016 Thesis http://umpir.ump.edu.my/id/eprint/16930/ http://umpir.ump.edu.my/id/eprint/16930/1/Customer%20churn%20classification%20in%20telecommunication%20company%20using%20rough%20set%20theory.pdf pdf en public masters Universiti Malaysia Pahang Faculty of Computer System And Software Engineering Makhtar, Mokhairi
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
advisor	Makhtar, Mokhairi
topic	QA Mathematics QA Mathematics
spellingShingle	QA Mathematics QA Mathematics Nur Syafiqah, Mohd Nafis Customer churn classification in telecommunication company using rough set theory
description	Churn is perceived as the behaviour of a customer to leave or to terminate a service. This behaviour causes the loss of profit to companies because acquiring new customer incurred high investment for advertisements and promotions compared to retaining existing ones. Thus, it is necessary to consider an efficient classification model to reduce the rate of churn. In the traditional approach of classification modelling, it do not produce straightforward result interpretation. Therefore, identifying the best classification model to reduce the rate of churn is indeed a challenging task. The main objective of this thesis is to propose a new classification model based on the Rough Set Theory to classify customer churn. This research utilized the Knowledge Discovery in Database (KDD) process involving data pre-processing, data discretization, attribute reduction, rule generation, classification process, as well as data analysis, using the Rough Set toolkit. The Rough Set theory elements consist of indiscernibility relation, lower and upper approximations, as well as reduction set. Those elements are applied to classify customer chum from uncertain and imprecise dataset. The results of the proposed model are compared with a few established existing approaches. The results of the study show that the proposed classification model outperformed the existing models and contributes to significant accuracy improvement. The model is tested using dataset form local telecommunication company which achieves 90.32%. In conclusion, the results proved that the classification model based on Rough Set Theory had been capable to classify customer chum compared to the existing model.
format	Thesis
qualification_level	Master's degree
author	Nur Syafiqah, Mohd Nafis
author_facet	Nur Syafiqah, Mohd Nafis
author_sort	Nur Syafiqah, Mohd Nafis
title	Customer churn classification in telecommunication company using rough set theory
title_short	Customer churn classification in telecommunication company using rough set theory
title_full	Customer churn classification in telecommunication company using rough set theory
title_fullStr	Customer churn classification in telecommunication company using rough set theory
title_full_unstemmed	Customer churn classification in telecommunication company using rough set theory
title_sort	customer churn classification in telecommunication company using rough set theory
granting_institution	Universiti Malaysia Pahang
granting_department	Faculty of Computer System And Software Engineering
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/16930/1/Customer%20churn%20classification%20in%20telecommunication%20company%20using%20rough%20set%20theory.pdf
_version_	1783732016734273536

Customer churn classification in telecommunication company using rough set theory

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