TRACKING EMPLOYMENT TRENDS IN MALAYSIA USING TEXT MINING TECHNIQUE; [Mengesan Trend Pekerjaan di Malaysia Menggunakan Teknik Perlombongan Teks]

• Published in: Journal of Quality Measurement and Analysis
• Main Author: Nasir S.A.M.; Yaacob W.F.W.
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2021
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202532438&partnerID=40&md5=6da1ff8fa21c46592c159c4c0b4c1c6d

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. © 2021, Penerbit Universiti Kebangsaan Malaysia. All rights reserved.