Algoritma Genetika untuk Menyelesaikan Permasalahan Penjadwalan Perkuliahan dan Praktikum
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Institusion
Universitas Sumatera Utara
Author
Apriani, Ridha (STUDENT ID : 071402019)
(LECTURER ID : 0031125982)
(LECTURER ID : 0029018304)
(LECTURER ID : 0031125982)
(LECTURER ID : 0029018304)
Subject
Schedulling
Datestamp
2022-12-14 07:12:44
Abstract :
In generally scheduling is done manually. This method has poor accuracy and a schedule caused collisions. In the lecture and lab scheduling caused collision schedule and teaching faculty, collision on the students schedule, a collision course with the time in college lab, and the availability of sufficient class. In this research explain about how the scheduling of lectures and practicums are scheduled by using Genetic Algorithm. The Genetic algorithm is a heuristic search algorithm based on the mechanism of natural selection which known biology evolution process. Genetic algorithm is used to get an optimal schedule is the process of population initialization, fitness evaluation, selection, crossover and mutation. The data of this research are lecturers, subjects, class and time taken from the database of information technology at University of North Sumatra. The data in advance through the process of genetic algorithm to obtain the appropriate result. The results of this research is generates the optimal schedule with the overall schedule of data subjects, faculty, classroom, day and time.
In generally scheduling is done manually. This method has poor accuracy and a schedule caused collisions. In the lecture and lab scheduling caused collision schedule and teaching faculty, collision on the students schedule, a collision course with the time in college lab, and the availability of sufficient class. In this research explain about how the scheduling of lectures and practicums are scheduled by using Genetic Algorithm. The Genetic algorithm is a heuristic search algorithm based on the mechanism of natural selection which known biology evolution process. Genetic algorithm is used to get an optimal schedule is the process of population initialization, fitness evaluation, selection, crossover and mutation. The data of this research are lecturers, subjects, class and time taken from the database of information technology at University of North Sumatra. The data in advance through the process of genetic algorithm to obtain the appropriate result. The results of this research is generates the optimal schedule with the overall schedule of data subjects, faculty, classroom, day and time.
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