Implementation of the Ant Colony System for Constraint-Based Lecture Timetabling in Higher Education

The lecture scheduling problem in higher education is a complex and recurring issue that requires optimal solutions to accommodate lecturer availability, room capacity, and student needs. This study implements the Ant Colony System (ACS) algorithm to address the scheduling problem by simulating the behavior of ants in finding optimal paths. The research method involves both literature study and field observation at STMIK Budidarma Medan. By modeling the scheduling constraints as nodes in a directed graph and using pheromone-based traversal to explore possible combinations, the system successfully generates class schedules that minimize conflicts and meet lecturer preferences. The results indicate that the ant algorithm is capable of producing optimal and practical solutions for dynamic and constraint-based scheduling needs.