Project Overview

This project is a website created as part of a Capstone Project to assist the initial screening process of job applicants’ CVs automatically, quickly, and more objectively. The system utilizes an Artificial Intelligence approach with the Support Vector Machine (SVM) method to analyze CV content, assess candidate suitability against job criteria, and provide initial recommendations that can help the HR team make decisions.

Problem Statement

The manual CV selection process is often time-consuming, prone to subjectivity, and inefficient when the number of applicants is very large. This condition makes initial screening the most time-draining stage, even though companies require a faster recruitment process without compromising selection quality.

Solution Offered

This website is designed to automatically analyze CVs based on required criteria. The system assesses the level of applicant suitability, then generates initial recommendations so that HR can focus on candidates with the best potential. Thus, the screening process becomes more measurable, consistent, and manageable for a large scale of applicants.

Website Features

The website displays four main features that support the end-to-end screening process:

1. CV Analyzer A feature to extract important information from the CV such as skills, experience, and education so that candidate data is easier to read and process.
2. AI Recommendation A feature that automatically provides suggestions for the best candidates for consideration in the next selection stage.
3. Applicant Ranking A feature for compiling candidate rankings based on suitability scores so that HR can quickly see candidate priorities.
4. Dataset Management A feature for managing the applicant dataset used for model training so that the system can be continuously adjusted and improved.

This project was developed by students of class S1IF-10-07, Informatics Engineering, Telkom University Purwokerto, namely Adam Bekti Laksono, Yogi Fakhri Aiman, Dwi Novianto, Adib Adzkia, and Sultan Ganiman Abigail.