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首页> 外文期刊>Journal of Quality Measurement and Analysis: JQMA >TRACKING EMPLOYMENT TRENDS IN MALAYSIA USING TEXT MINING TECHNIQUE
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TRACKING EMPLOYMENT TRENDS IN MALAYSIA USING TEXT MINING TECHNIQUE

机译：使用文本挖掘技术跟踪马来西亚的就业趋势

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摘要

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.
机译：2019冠状病毒疾病已经改变了我们今天生活的世界。特别是，在全国范围内部署的移动控制命令（MCO）也会对就业创造产生间接影响。由于大量毕业生已经毕业，而那些没有工作的人将更难找到工作。本研究试图通过从JobStreet网站随机抽取2020年9月至10月的招聘广告，调查马来西亚大流行期间的就业趋势。使用文本挖掘技术对1050份文档样本进行了分析，分析了两个驱动因素：职位和位置。结果显示，提供最多职位的是经理，提供最多职位的地方是吉隆坡，其次是雪兰莪州。使用K-Mediods聚类进行进一步分析，根据位置对职位进行聚类，以说明马来西亚的就业趋势，从而得出类似的结果。

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