Implementation of Web Scraping on Job Vacancy Sites Using Regular Expression Method

Abstract

Job vacancy information is now not only found in newspapers, brochures, or visiting companies but information can be found on the internet. On the internet many third-party websites that provide job vacancy information that can help job seekers get information, some third party websites sometimes do not have vacancy information on the same company as other websites, because the company that owns the vacancy does not provide their company's job vacancy information to all third-party websites, so job seekers visit many websites to meet each other to get the information they want, so job seekers visit many websites to find each other to get the information they want, which takes a long time. To simplify and shorten the time in searching for information, we can utilize a web that can display more than one third-party web so that job seekers do not need to open many third-party webs. The purpose of this research is to implement Web Scraping to retrieve data about job vacancy information with Regular Expression method and build a web-based information system to display data obtained from Web Scraping. The results of Web Scraping experiments with the Regular expression method on three third-party websites namely Jobstreet, Kalibrr, and Glints were able to retrieve data from the three websites. The resulting accuracy is very good, on Jobstreet and Kalibrr produces 100% accuracy in providing correct results while Glints produces 99.4% accuracy. The data collected from the web scraping process is stored in the database and then displayed on the developed web.