TOOL DEVELOPMENT FOR UNIVERSITY COURSE TIMETABLING PROBLEM CASE STUDY: ITB UNIVERSITY COURSE TIMETABLING - SUCIPTO, LUBIS
University timetabling in ITB generally submitted by each Department (Prodi). But for first level course (TPB) and all public lecture scheduled by Directorate of Education (Dirdik). This can make a problem because many course clashed because it is regulated by each Department. Also the schedule are not evenly distributed where some students with dense schedule on a certain day and empty the other days. Timetabling algorithm that will be implemented is greedy algorthm and genetic algorithm. Both algorthm was optimization algorithm that often used for searching solutions for any problem. All problem from ITB university course timetabling will be analyzed to be constraint for each algorthm while finding the solution. The result from this final project is that algorthm can make schedule with optimal whre have least constraint violation. The average of vitness value form greedy algorithm result is 0.967. While the genetic algorthm result in 100th , 300th, and 500th generation is 0.986, 0.913 and 0.939. The result from combining two algorthms where initiation of genetic used result from greedy algorithm is more optimal and get better result. The average fitness value from 100th generation is 0.986. From the result, the most constraint violation in the solution is where course that have some course number with same Departement participant must scheduled at the same time. This is because the lack of available room. Adding the available room will make the better result from the tool.