Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth

Data mining (DM) is the extraction of hidden predictive information from large databases that has becoming a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. A predictive model makes a prediction about values of data usi...

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Main Author:	Roznim, Mohamad Rasli
Format:	Thesis
Language:	eng eng
Published:	2005
Subjects:	QA71-90 Instruments and machines
Online Access:	https://etd.uum.edu.my/1343/1/ROZNIM_BT._MOHAMAD_RASLI.pdf https://etd.uum.edu.my/1343/2/1.ROZNIM_BT._MOHAMAD_RASLI.pdf
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id	my-uum-etd.1343
record_format	uketd_dc
spelling	my-uum-etd.13432013-07-24T12:11:32Z Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth 2005-07-14 Roznim, Mohamad Rasli Faculty of Information Technology Centre for Graduate Studies QA71-90 Instruments and machines Data mining (DM) is the extraction of hidden predictive information from large databases that has becoming a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. A predictive model makes a prediction about values of data using known results found from historical data where the best possible outcome based on the previous data is derived. Telekom Malaysia (TM) is Malaysia's premier communications provider that provides the digital backbone and communication facilities. Direct Exchange Line (DEL) is one of its core telephony services that handle massive volume and variety of data in its daily operations. Therefore, it is hard to reveal knowledge structures that can guide decisions in conditions of limited certainty. The main objective of this study is to identify the most appropriate DM technique between logistic regression, decision tree and neural networks for predicting DEL growth based on five physical attributes namely exchanges, subscribers, new installation, cutting, and availability of cable or ports (ECP) that constitute of 672 instances leading to a target (either increase or decrease). The result of this study is important in assisting the prediction of DEL growth in TM specifically in Penang, thus leading on better understanding on the future of the market based on the current and previous situation. 2005-07 Thesis https://etd.uum.edu.my/1343/ https://etd.uum.edu.my/1343/1/ROZNIM_BT._MOHAMAD_RASLI.pdf application/pdf eng validuser https://etd.uum.edu.my/1343/2/1.ROZNIM_BT._MOHAMAD_RASLI.pdf application/pdf eng public masters masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA71-90 Instruments and machines
spellingShingle	QA71-90 Instruments and machines Roznim, Mohamad Rasli Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth
description	Data mining (DM) is the extraction of hidden predictive information from large databases that has becoming a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. A predictive model makes a prediction about values of data using known results found from historical data where the best possible outcome based on the previous data is derived. Telekom Malaysia (TM) is Malaysia's premier communications provider that provides the digital backbone and communication facilities. Direct Exchange Line (DEL) is one of its core telephony services that handle massive volume and variety of data in its daily operations. Therefore, it is hard to reveal knowledge structures that can guide decisions in conditions of limited certainty. The main objective of this study is to identify the most appropriate DM technique between logistic regression, decision tree and neural networks for predicting DEL growth based on five physical attributes namely exchanges, subscribers, new installation, cutting, and availability of cable or ports (ECP) that constitute of 672 instances leading to a target (either increase or decrease). The result of this study is important in assisting the prediction of DEL growth in TM specifically in Penang, thus leading on better understanding on the future of the market based on the current and previous situation.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Roznim, Mohamad Rasli
author_facet	Roznim, Mohamad Rasli
author_sort	Roznim, Mohamad Rasli
title	Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth
title_short	Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth
title_full	Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth
title_fullStr	Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth
title_full_unstemmed	Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth
title_sort	predictive modeling on telekom malaysia direct exchange line growth
granting_institution	Universiti Utara Malaysia
granting_department	Faculty of Information Technology
publishDate	2005
url	https://etd.uum.edu.my/1343/1/ROZNIM_BT._MOHAMAD_RASLI.pdf https://etd.uum.edu.my/1343/2/1.ROZNIM_BT._MOHAMAD_RASLI.pdf
_version_	1747827125703933952

Predictive Modeling on Telekom Malaysia Direct Exchange Line Growth

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