Optimizing CV Matching with Job Vacancies Using the Boyer-Moore Algorithm
Abstract
According to a survey conducted by a public survey agency, there was a decline in percentage from 37% to 20%, indicating a gap still exists between skills required by the job market and those possessed by job seekers. To address this issue, this study aims to assess the alignment between data from curriculum vitae (CV) and job vacancies. Boyer-Moore algorithm is implemented through a web-based system. System extracts text from a PDF file, which is used in the application of Boyer-Moore algorithm. System also retrieves selected job vacancy data and generates keywords using YAKE (Yet Another Keyword Extractor). Before processing with Boyer-Moore algorithm, all data undergoes pre-processing. Algorithm's output is either a "match found" or "no match found." Similarity score is determined by dividing number of matching keywords by total number of keywords. Additionally, system recommends other job options, aiming to suggest alternative vacancies that may better match the CV. Recommendations based on highest percentage of keyword matches from all job vacancy data stored in the system, which are sorted accordingly. Boyer-Moore algorithm was successfully implemented in the job vacancy system, and the system's performance evaluation, using 100 job vacancy data entries, yielded an average processing time of 2.84 seconds.
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