Journal of Applied Science, Engineering, Technology, and Education
Vol. 8 No. 2 (2026), Pages 443-452 · 2026-08-31
An NLP-Based Intelligent Recruitment System Using Semantic Similarity for Ranking Interview Candidates
- Publication History
- Published online: August 31, 2026
- DOI
- https://doi.org/10.35877/454RI.asci4868
- Copyright
- Copyright (c) 2026 Silvester Dian Handy Permana, Anies Lastiati, Umar Al Faruq (Author)
- User License
- https://creativecommons.org/licenses/by-nc-sa/4.0
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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How to Cite
Silvester Dian Handy Permana, Anies Lastiati, & Umar Al Faruq. (2026). An NLP-Based Intelligent Recruitment System Using Semantic Similarity for Ranking Interview Candidates. Journal of Applied Science, Engineering, Technology, and Education, 8(2), 443–452. https://doi.org/10.35877/454RI.asci4868
Copyright & license
Copyright (c) 2026 Silvester Dian Handy Permana, Anies Lastiati, Umar Al Faruq (Author) 
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
