Tracking employment trends in Malaysia using text mining technique

Syerina Azlin Md Nasir, and Wan Fairos Wan Yaacob, (2021) Tracking employment trends in Malaysia using text mining technique. Journal of Quality Measurement and Analysis, 17 (1). pp. 177-187. ISSN 1823-5670


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The Covid-19 pandemic has changed the world we live in today. In particular, Movement Control Orders (MCOs) that have been deployed nationwide also have an indirect impact on the job creation. With the large number of graduates who have graduated and those who do not have a job will make it even more difficult to get a job. This study attempts to investigate the employment trends during the pandemic in Malaysia by extracting job advertisements randomly from JobStreet website from September to October 2020. A sample of 1050 documents was analysed using text mining technique on two driving factors, job title and location. The results reveal that the highest number of positions offered are managers and the place that offered the most jobs was in Kuala Lumpur followed by Selangor. Further analysis is performed using K-Mediods Clustering to cluster the job titles against the location to illustrate the employment trends in Malaysia, which resulted in similar outcomes.

Item Type:Article
Keywords:Clustering; Job vacancy; Text mining
Journal:Journal of Quality Measurement and Analysis
ID Code:17840
Deposited By: ms aida -
Deposited On:06 Jan 2022 01:25
Last Modified:07 Jan 2022 00:40

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