New Employee Selection System using WP and SAW Methods Based on Web at PT Lanang Agro Bersatu - Ria Sapitri; Syarifah Putri Agustini Alkadri; Putri Yuli Utami (Journal of Artificial Intelligence and Engineering Applications (JAIEA), 2025)
Employees are valuable assets for a company, requiring careful selection based on educational background and experience to ensure proper placement and avoid issues. At PT Lanang Agro Bersatu, the selection process involves approximately 30 candidates monthly. This study developed a web-based employee selection system using the Weighted Product (WP) and Simple Additive Weighting (SAW) methods. The system aims to calculate weight values for criteria such as Education, Work Experience, Age, Health, GPA, Academic Tests, and Psychological Tests, providing accurate rankings to simplify decision-making. The top candidate, Khusnul Wasillah, achieved the highest preference value of 0.1563, calculated through combined SAW and WP methods. System testing using black box and equivalence partitioning methods showed 100% accuracy.