Pengembangan Rest API untuk Ekstraksi Informasi dari Resume Menggunakan Java Spring Boot - Ciptanto, Evry Nazyli; Nasrul, Nasrul (LPPM STT Terpadu Nurul Fikri, 2024)
Career platforms like Klob are among the modern recruitment methods. In the Klob career platform context, users face challenges when filling out their profile data. The main challenge is manual filling, which slows the registration and job application process. The problem required development to integrate information extraction from user resumes as an efficient solution. The Java Spring Boot programming language built a resume information extraction backend development system. This integration also utilized Natural Language Processing (NLP) recognition algorithms using OpenNLP to improve understanding of the context of sentences on resumes. One of the OpenNLP methods used was Named Entity Recognition (NER) to identify and extract named entities. The Rule-Based Extraction approach was also specified to extract information from text based on rules. This research was based on the results of testing conducted through the User Acceptance Test (UAT), and it was found that the percentage score given had an excellent interpretation level of 91.1%. This research provides a comprehensive overview of the effectiveness of the proposed solution in overcoming manual filling obstacles, improving user experience, and speeding up registration.