Nik Nurul Syuhada Binti Mohd Ali, <br/><br/>
Future workforce demand and analysis / 
Nik Nurul Syuhada Binti Mohd Ali 
 - xi, 53 pages :  illustrations ;  1 CD-ROM 
<br/><br/> Centre for Mathematical Sciences 
<br/><br/>Bachelor of Applied Science in Data Analytics with Honours -- Universiti Malaysia Pahang – 2023 
<br/><br/>Includes bibliographical references 
<br/><br/> The workforce planning model is intended to provide simple and practical guidance on  how to organise the workforce so that personnel and skills are matched with an  organization's present and future strategic business objectives. Employers may bridge  talent shortages and identify individuals who can succeed with the right professional  development by using workforce planning analysis to help them build the appropriate  training and employee development programmes. Therefore, it is vital to select the  appropriate model as it resembles with the features of the workforce planning model. This  study assesses the forecasting performance of workforce skills using the logistic  regression model. The proposed logistic regression model has been applied to the data of  workforce skill demand from year 2018 to 2022. This study employed data visualization  for skills prediction on the most common data skills labour needed for the industry. In  this study, the correlation of data science skills is presented that we believe can support  the industry standardization for every coursework. Monthly income was found to have  the highest score, indicating that it has the most significant impact on increasing  workforce demand. 
<br/><br/><label>ISBN: </label>THE0010013 (Local) 
<br/><br/><label>Subjects--Corporate Names: </label><br/>Centre for Mathematical Sciences--Dissertations
<br/><br/><label>Subjects--Topical Terms: </label><br/>Universities and colleges--Dissertations<br/>Final Year Project--Thesis