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PENGEMBANGAN SISTEM REKRUTMEN TERINTEGRASI BERBASIS LOW-CODE DAN NATURAL LANGUAGE PROCESSING (NLP)
This system development aims to design and develop a smart recruitment and corporate helpdesk system to overcome communication inefficiencies and manual candidate evaluation in the Human Resource (HR) department. The system development method utilizes the Waterfall Software Development Life Cycle (SDLC) combined with artificial intelligence technology. The system integrates a Retrieval-Augmented Generation (RAG) chatbot for automated responses and an AI-based CV Screening module utilizing the Gemini Large Language Model (LLM) for semantic analysis and the Simple Additive Weighting (SAW) method for candidate qualification weighting. All processes are orchestrated into an end-to-end automated workflow using the n8n low-code platform with a React.js web interface. Testing results demonstrate that the RAG chatbot accurately responds to 100% of question scenarios with a latency of 3-15 seconds. Furthermore, the workflow automation successfully reduces the CV document processing time to an average of only 38.7 seconds per candidate. The hybrid approach of LLM and SAW proves effective in eliminating subjectivity bias compared to conventional keyword matching. In conclusion, this integrated system significantly improves operational efficiency in recruitment and corporate communication.
FAKULTAS SAINS DAN TEKNOLOGI, UIN SUNAN KALIJAGA YOGYAKARTA
NIM.: 22106050089 Zhafran Pradistyatama Kuncoro
PENGEMBANGAN SISTEM REKRUTMEN TERINTEGRASI BERBASIS LOW-CODE DAN NATURAL LANGUAGE PROCESSING (NLP) (Text)
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004 Pemrosesan Data, Ilmu Komputer, Teknik Informatika