Mauluddin, Syahrul
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PENERAPAN ALGORITMA GENETIK UNTUK OPTIMASI SISTEM INFORMASI PENJADWALAN KULIAH (STUDI KASUS PROGRAM STUDI SISTEM INFORMASI UNIVERSITAS KOMPUTER INDONESIA) Effendi, Muhammad Ridwan; Agustino, Rano; Mauluddin, Syahrul
JIK: Jurnal Ilmu Komputer Vol 4, No 02 (2019): JIK : JURNAL ILMU KOMPUTER
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/komp.v4i02.3139

Abstract

The college scheduling activity is a routine activity every semester that is very complicated and draining the mind. In the current system, the information system study program of Indonesian computer universities has used a lecture scheduling information system application for the college scheduling process. However, the application has a disadvantage, namely the scheduling process is still done by manually selecting space, days and hours, and has not implemented the optimization algorithm for the scheduling process, so the scheduling process still requires a long time and is not optimal. Given the importance of this scheduling process, it is necessary to do the optimization steps for scheduling lectures appropriately so that the process of scheduling lectures is faster and schedule conflicts can be minimized so that teaching and learning activities can run well. For this research, we intend to apply genetic algorithms to the scheduling process with the aim of optimizing the lecture scheduling process in the information systems study program. In this research method, the stages of the research will be described as the system development method, research location, and data collection techniques.      The results of this study are that there are no more conflicting schedules after 10 trials were marked with fitness with a value of 0. The conclusion of this research is that by applying genetic algorithms to the college scheduling application, the process of scheduling lectures can be done automatically until there is no schedule conflict and out of 10 experiments, the average time for lecturing schedule was 58.454 seconds (less than 1 minute) and the average was achieved in generation 1,2,3. Keywords: genetic algorithms, lecture scheduling, chromosomes