Optimasi Pemetaan Tugas Mengajar Dosen Menggunakan Memetic Algorithm - Okvio Akbar Karuniawan; Nurul Hidayat; Marji Marji (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Submission of information relating to teaching and learning activities is very important, one of the first things to consider is scheduling. At Faculty of Computer Science (FILKOM) Brawijaya University, the assignment process is still manually designed where it requires some substantial time, therefore it needed a right optimization methods in dealing with this case. This assignment problem can be solved by a population-based heuristic methods, Memetic Algorithm (MA) which has been applied in various fields such as scheduling and assignments. The data used in this study is the data division of lecturers teaching tasks as a priority of lecturer's teaching interests to a course. From the obtained data, it determined constraints such a lecturer's teaching priority, the maximum and minimum amount of credits, and the number of course that can be taken to calculate fitness value for each particles. Through the obtained results, it had parameter tested to find the effect of tested parameters on the resulted fitness values. From MA parameters test results, it obtained the best population number as 100, best iteration number as 100, and combination of parameter cr and mr as 0,8 and 0.2 with resulted fitness value as 87830. From the results of system, The fitness value of the test is optimal solution of generation 100 because the stop conditioning memetic algorithm is a maximum iteration. But the results do not guarantee if the value of Cr is getting smaller and the greater the value of Mr will produce better fitness.