Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid

Johor is a state that located in southern west in peninsular Malaysia. The population growth increased at rate of 2.2% for period from 2010 to 2020. One of the main problems in world is population growth. This is important issue that must be alerted to. Growth model is one of the methods to estimate...

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Main Author:	Abdul Hamid, Aina Haziqah
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Population geography Migration
Online Access:	https://ir.uitm.edu.my/id/eprint/95189/1/95189.pdf
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id	my-uitm-ir.95189
record_format	uketd_dc
spelling	my-uitm-ir.951892024-05-14T01:21:49Z Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid 2024 Abdul Hamid, Aina Haziqah Population geography. Migration Johor is a state that located in southern west in peninsular Malaysia. The population growth increased at rate of 2.2% for period from 2010 to 2020. One of the main problems in world is population growth. This is important issue that must be alerted to. Growth model is one of the methods to estimate the population and also can represents the data in mathematical way. Estimate population can help the government to take first step to avoid overpopulation or underpopulation in a country. Then, it also can help for make sure the country stable. Thus, in this study there are three types of growth model that had been used to estimate population growth in Johor. The growth models are Exponential, Logistics and Gompertz. Moreover, to determine the best growth models among them is based on value of the Root Mean Square Error (RSME). Based on the results, it shows Logistics Growth Model is the best because of the value or RSME is the lowest other than models while the value for adjusted R2 is the highest and closer to 1. 2024 Thesis https://ir.uitm.edu.my/id/eprint/95189/ https://ir.uitm.edu.my/id/eprint/95189/1/95189.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Mathematics Salahudin, Nur Atikah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Salahudin, Nur Atikah
topic	Population geography Migration
spellingShingle	Population geography Migration Abdul Hamid, Aina Haziqah Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid
description	Johor is a state that located in southern west in peninsular Malaysia. The population growth increased at rate of 2.2% for period from 2010 to 2020. One of the main problems in world is population growth. This is important issue that must be alerted to. Growth model is one of the methods to estimate the population and also can represents the data in mathematical way. Estimate population can help the government to take first step to avoid overpopulation or underpopulation in a country. Then, it also can help for make sure the country stable. Thus, in this study there are three types of growth model that had been used to estimate population growth in Johor. The growth models are Exponential, Logistics and Gompertz. Moreover, to determine the best growth models among them is based on value of the Root Mean Square Error (RSME). Based on the results, it shows Logistics Growth Model is the best because of the value or RSME is the lowest other than models while the value for adjusted R2 is the highest and closer to 1.
format	Thesis
qualification_level	Bachelor degree
author	Abdul Hamid, Aina Haziqah
author_facet	Abdul Hamid, Aina Haziqah
author_sort	Abdul Hamid, Aina Haziqah
title	Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid
title_short	Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid
title_full	Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid
title_fullStr	Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid
title_full_unstemmed	Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid
title_sort	comparison of gompertz, exponential, logistics and linear growth models to estimate population of johor in 2023 / aina haziqah abdul hamid
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Mathematics
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/95189/1/95189.pdf
_version_	1804889950950260736

Comparison of gompertz, exponential, logistics and linear growth models to estimate population of Johor in 2023 / Aina Haziqah Abdul Hamid

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