Technical report: the comparison between exponential growth and logistic growth model for Malaysia’s population / Hazura Akmal Muda, Hernidayati Sugiono and Julaikha Liyana Ali

Muda, Hazura Akmal and Sugiono, Hernidayati and Ali, Julaikha Liyana (2016) Technical report: the comparison between exponential growth and logistic growth model for Malaysia’s population / Hazura Akmal Muda, Hernidayati Sugiono and Julaikha Liyana Ali. [Student Project] (Unpublished)

Abstract

Many countries are experiencing out of ordinary rapid demographic change. It is important to know the human population in future. There exist many models for describing growth rates of populations over time. This project will aim to find the most suitable model between exponential growth model and logistic growth model for population growth of Malaysia using data from 1993 to 2015. The exponential growth model predict of growth rate of 0.02719 per annum and also predicted the population to be 46 790 776.21 in 2025. Logistic growth model, which describes the population that increase rapidly until it reaches carrying capacity. We find the carrying capacity by graphical trial and error procedure. Then we predicted the population to be 38 697 302.09 using the same growth rate as exponential model. For future work, logistic growth model can be used to measure human population instead of using exponential model.

Metadata

Item Type: Student Project
Creators:
Creators
Email / ID Num.
Muda, Hazura Akmal
2014828298
Sugiono, Hernidayati
2014213126
Ali, Julaikha Liyana
2014619302
Contributors:
Contribution
Name
Email / ID Num.
Advisor
Rosli, Aimi Zulliayana
UNSPECIFIED
Advisor
Wan Ramli, Wan Khairiyah Hulaini
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Study and teaching
Q Science > QA Mathematics > Equations
Q Science > QA Mathematics > Wavelets (Mathematics)
Divisions: Universiti Teknologi MARA, Kelantan > Machang Campus > Faculty of Computer and Mathematical Sciences
Programme: Mathematics Project (MAT660)
Keywords: Demographic, population, Malaysia, growth model
Date: 2016
URI: https://ir.uitm.edu.my/id/eprint/110505
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