Implementasi Algoritma Genetika untuk Penjadwalan Perkuliahan (Studi Kasus : Program Studi Sarjana Matematika di Universitas Sumatera Utara)

Abstract

Scheduling lectures effectively and efficiently is a major challenge because of the complexity of arranging time, space and lecturers according to various courses and number of students. According to observations made in the Undergraduate Mathematics Study Program at the University of North Sumatra, there are still conflicts in lecture scheduling in one of the courses, especially in terms of space and time. The aim of this research is to optimize the lecture schedule so that there are no schedule conflicts between lecturers, students and rooms and appropriate room capacity. The genetic algorithm was chosen because of its ability to find optimal solutions through calculating the highest fitness of each individual followed by the process of selection, crossover, mutation and with the help of GeneRepair to ensure that all solutions produced are valid and feasible. The results of this research show that genetic algorithms can produce more optimal lecture schedules. The result is a solution for students to be given sufficient rest time to change the first and subsequent courses, especially with a weight of 3 credits and also to avoid clashes between students, lecturers and the room. Limited space will be difficult to adjust for students who will occupy it according to the schedule given, so students must get room capacity and room facilities that are appropriate to the number of students who will use the room.