Sistem Rekomendasi Lowongan dan Pencarian Talent Alumni Menggunakan Content-Based Filtering dengan Weighted Feature Matching
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Muhammad Ihsan Nurulhuda
*
Universitas Islam Indonesia, Yogyakarta,
Indonesia
(*) Corresponding Author
Abstract
The development of information technology encourages the need for systems that are capable of managing alumni data while supporting the utilization of such data for career development purposes. In IKATEKSI UII, alumni data management and membership services were previously not integrated into a single platform, resulting in limited utilization of alumni data for career information and talent searching needs. This study aims to develop a web-based alumni management and membership platform by implementing the Content-Based Filtering (CBF) method using the Weighted Feature Matching approach on job recommendation and Talent Search features. This study integrates alumni data management and membership services with an attribute-based matching mechanism using Content-Based Filtering and Weighted Feature Matching to support job vacancy recommendations and talent searches based on profile suitability. The system development method used is the Waterfall model, consisting of analysis, design, implementation, and testing stages. The system was developed using the Laravel framework with MySQL as the database. The results show that the developed platform successfully integrates alumni data management, membership services, and career development features based on profile attribute matching. The evaluation of the CBF method on the Talent Search feature achieved a Precision value of 1.000, Recall of 0.706, and F1-Score of 0.828. In addition, Black Box Testing results indicate that all main system functions operate according to the designed requirements.
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