Course Scheduling Information System Using Genetic Algorithms - Freddy Wicaksono; Bayu Permana Putra (Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon, 2021)
University X is a private university which has 8 faculties, namely Economics, Engineering, Social Sciences, Faculty of Social and Political Sciences, Fikes, Law, Islam and Vocational Studies. One of the leading study programs at the University X is the Informatics Engineering Study Program at the Faculty of Engineering which is currently experiencing problems when the process of dividing space and hour schedules is still manual.The problems that arise include the accumulation of lecture hours for a lecturer who takes more than one course. Another problem is the disruption of the lecture process at the beginning of the semester due to the tentative scheduling system. The preparation of lecture schedules at the Faculty of Engineering, University X is still done semi-manually using Microsoft Excel, so it will take several days to make a schedule. Meanwhile, making a schedule must be done quickly and optimally because it is used for lecture activities, the solution that can overcome the above problems is by creating a Course Scheduling Information System Using Genetic Algorithms. The genetic algorithm is one of the most appropriate algorithms used in solving complex optimization problems, which are difficult to do with conventional methods. The nature of genetic algorithms is looking for possibilities from potential solutions to get the optimal for solving problems. The scope of all viable solutions, i.e. the objects between matching solutions, is called the search space. Each point in the search space represents a viable solution. The limitations of the built problem are: This system is operated by the administrative staff of the study program at the Faculty of Engineering, University X. This system is made using the Codeigniter framework, Responsive Bootstrapping (display) and MySQL as the database and the method used by this system is the genetic algorithm method. The final result of this research is that it is helpful and easy to apply as a tool in helping the optimization process of lecture scheduling in order to minimize schedule collisions in lectures at the Faculty of Engineering, University X