Simulating the Upcoming Trend of Malaysia’s Unemployment Rate Using Multiple Linear Regression

• Published in: Communications in Computer and Information Science
• Main Author: Mohamad Adib N.S.Y.; Mohd Ibrahim A.A.; Abdul Halim M.H.
• Format: Conference paper
• Language: English
• Published: Springer Science and Business Media Deutschland GmbH 2021
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119423046&doi=10.1007%2f978-981-16-7334-4_13&partnerID=40&md5=f58537095242e9e826f5a09494e069b3

This research paper presents the approach of applying the simulation technique to predict the upcoming trend of Malaysia’s unemployment rate. The recent Malaysia’s unemployment rate has fluctuated at quite a high rate ever since the COVID-19 pandemic occurred. Population growth, Growth Domestic Product (GDP), inflation rate, interest rate, exchange rate, investment, government expenditure and most importantly the number of COVID-19 cases act as the independent variables in this paper. The Multiple Linear Regression (MLR) is used to determine the significance of each variable to be included in the model and also to simulate the upcoming trend of Malaysia’s unemployment rate. The result of the analysis shows that the upcoming five years trend of Malaysia’s unemployment rate will continue to increase in the future based on the average value of the simulations conducted. © 2021, Springer Nature Singapore Pte Ltd.