Penerapan Algoritma Greedy pada Sistem Penjadwalan Cerdas Asisten Laboratorium Berbasis Kompetensi

Abstract

Manual scheduling of laboratory assistants often leads to several issues, including schedule conflicts, uneven workload distribution, and mismatches between assistant competencies and practicum requirements. This study aims to develop a web-based laboratory assistant scheduling system by applying a Greedy algorithm that integrates multiple parameters, including competence, time preference, experience, and workload. The scheduling problem is formulated using an objective function and constraints to ensure a structured and reproducible solution. The Greedy algorithm is implemented using a hierarchical priority mechanism to select the best candidate at each assignment step. The evaluation was conducted using real-world data consisting of more than 200 practicum schedules and 30 laboratory assistants. The results show that the system successfully generates conflict-free schedules, with 66.7% of assignments meeting strict competency criteria and 80% matching assistants' primary time preferences. The workload distribution is also relatively balanced among assistants. In terms of efficiency, the system reduces scheduling time from 2–3 days to less than 10 second, achieving more than 99% improvement  compared to manual methods. These findings indicate that the Greedy algorithm is effective in producing a fast, objective, and adaptive scheduling system.