Sistem Rekomendasi Pengembangan Skill Digital Berbasis Metode SAW untuk Meningkatkan Daya Saing Tenaga Kerja di Era Ekonomi Digital

Abstract

The massive digital transformation that has occurred in the industrial world has created a need for workers with high digital skills. Amidst the challenges of the Industrial Revolution 4.0 and the acceleration of the digital economy, digital skill development is an important aspect in increasing the competitiveness of the workforce. However, many individuals have difficulty determining the priority of skill development appropriately. Therefore, this study aims to develop a web-based recommendation system using the Simple Additive Weighting (SAW) method to help individuals determine the priority of digital skill development. This system utilizes four main criteria, namely: (1) Mastery of Digital Skills, (2) Work Experience, (3) Interest in Skills, and (4) Ownership of Digital Certification. Each criterion has its own weight, namely 0.35, 0.25, 0.20, and 0.20. Overall, this system has succeeded in helping the decision-making process for developing digital skills objectively and systematically. Not only is it beneficial for job seekers or professional workers, this system also has the potential to be used by training institutions, educational institutions, and the government in designing policies to improve digital competence. However, this system still has limitations, such as not covering soft skill aspects and not being integrated with external platforms. In the future, development can be done by adding new criteria, data integration from online learning platforms, and using machine learning methods to provide more adaptive and personalized recommendations.