An NLP-Based Intelligent Recruitment System Using Semantic Similarity for Ranking Interview Candidates

Silvester Dian Handy Permana; Anies Lastiati; Umar Al Faruq

doi:10.35877/454RI.asci4868

Authors

Silvester Dian Handy Permana Universitas Trilogi
Anies Lastiati Universitas Trilogi
Umar Al Faruq Universitas Trilogi

DOI:

https://doi.org/10.35877/454RI.asci4868

Keywords:

Natural Language Processing, Intelligent Recruitment System, Semantic Similarity, Interview Answer Analysis, Candidate Ranking

Abstract

The high number of applicants for a job vacancy makes it difficult for the Human Resources (HR) team to find the best candidates who can be called for the interview process. This highlights the need for computational analysis that can semantically understand and compare applicant responses. This research implements Natural Language Processing into an artificial intelligence (AI)-based model that is capable of selecting applicant candidates in open-ended questions. Data from 100 applicants served as input. The NLP model was empirically tested by reviewing the recommendations provided and the candidates' responses. The model proved effective in assisting HR in candidate selection.

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