Modelling Workforce For Transportation Sector In Malaysia (Considering Covid-19 Pandemic)

• Published in: 2022 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2022 - Proceedings
• Main Author: Hadrawi M.F.; Sarifah Radiah Shariff S.; Muhamad N.A.; Abdullah N.A.; Damanhuri N.A.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134728898&doi=10.1109%2fI2CACIS54679.2022.9815486&partnerID=40&md5=6f52122ccb91c4b99783d2228d14bb87

The Covid-19 pandemic is worrying the workforce, especially in the transportation sector since transportation has been one of Malaysia's crucial sectors. The problem of losing jobs during the Covid-19 pandemic largely contributes to low economic Malaysians, especially in the urgent need for change. Thus, adopting a strategic approach is needed to plan and manage workforce trends to prevent a drop in the economy. This study examines the workforce pattern in the transportation sector in Malaysia, comparing them using time series models and forecasting them using the best fit time series model. It studies explicitly the export and import volume in Malaysia from the year 2010 until 2020 and the number of workforces in the transportation sector in Malaysia from 2012 until 2020. The data were used to model and forecast the export and import volume and the number of workers in the transportation sector in Malaysia. It is found that ARIMA (0, 1, 1) model was able to produce the forecasted values for the year 2020 for export volume in Malaysia based on the values of RMSE and Holt's (α = 0.34, β = 0.01, γ = 0.3) were able to forecast for export volume in Malaysia when the MAE and MAPE values were considered. Also, it is found that ARIMA (2, 1, 3) model was able to produce the forecast value for import volume in Malaysia for 2020 when the MAE and RMSE were used while Holt's model (α = 0.41, β = 0.04, γ = 0.5) when MAPE value was considered. Lastly, ARIMA (1,1,1) was used as the selection criteria for forecasting the number of workers in the transportation sector in Malaysia for 2020 when RMSE and MAPE were used Holt's (α =0.62, β = 0.00000000000000034694) model meanwhile when MAE value was considered. © 2022 IEEE.