Optimasi Penjadwalan Perkuliahan Pada Universitas Handayani Makassar Menggunakan Algoritma Particle Swarm Optimization

Abstract

Lesson planning is a regular task that every educational institution does right from the beginning of the semester. However, creating an optimal study schedule is quite difficult because there are many interrelated variables that require careful management. Current class scheduling at Handayani University Makassar is still done manually, including searching for empty columns and placing class schedules in those columns. The director of BAAK UHM, who was responsible for preparing the conference program, felt overwhelmed. Because the planning done so takes a lot of time. Therefore, the established course program must be regularly revised. One method considered to provide a solution to scheduling problems is swarm optimization (PSO). PSO if translated means Particle Swarm Optimization. This algorithm can solve the problem by randomly forming particles in the initial population, evaluating appropriate values, and updating particle velocities and positions. This is intended to address the issue of proper function of each particle. The data includes 225 course data plus 1 speaker's request schedule data. This study was successful in achieving a course schedule consistent with the course conditions and policies at UHM. From the test results, the lesson planning application using the PSO algorithm can provide an optimal class schedule that is consistent with the teacher's teaching schedule preferences. The calculation time used is less than 5 seconds.