OPTIMIZING COURSE SCHEDULING FACULTY OF ENGINEERING UNSOED USING GENETIC ALGORITHMS
In carrying out an activity regularly and smoothly, it is necessary to make an activity schedule that can manage the time of one activity with another so that unwanted things do not happen such as the same time, the same place, and others. Making a schedule of activities is quite easy to do if there are not too many entities involved and if the entities are not tied to each other, but for larger cases, creating a schedule of activities manually will take quite a lot of time and can result in errors in the schedule or shortages. effectiveness in the resulting schedule. This is commonly experienced in making course schedules at universities because there are a lot of course data and lecturers can teach several courses at once and at different times, therefore in making course schedules can be done by applying genetic algorithms so that the time required needed in making the course schedule shorter and the results obtained can be more optimal than the results of making the course schedule manually. In this study, the optimal course schedule was obtained in the 31st generation using data on rooms, courses, study time, lecturers, and departments so that one chromosome has 154 gen, then the population length is made up to 9 individuals or chromosomes, the mutation rate is set at 0.1, and the method used in the individual selection stage is the tournament selection method where the tournament size is set at 3. The fitness value is taken so that a schedule is said to be optimal, i.e. if the fitness value is equal to 1 because then it shows that there are no errors or problems (such as time, lecturers, conflicting rooms) that occur in the schedule.
J. Xu, “Improved Genetic Algorithm to Solve the Scheduling Problem of College English Courses,” Complexity, vol. 2021, 2021, doi: 10.1155/2021/7252719.
I. K. W. I Gusti Ayu Desi Saryanti, “Penerapan Metode Algoritma Genetika untuk Penjadwalan Mengajar,” Simetris : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, vol. 8, no. 1, 2017.
S. N. Jat and S. Yang, “A hybrid genetic algorithm and tabu search approach for post enrolment course timetabling,” Journal of Scheduling, vol. 14, no. 6, 2011, doi: 10.1007/s10951-010-0202-0.
W. Wen-Jing, “Improved adaptive genetic algorithm for course scheduling in colleges and universities,” International Journal of Emerging Technologies in Learning, vol. 13, no. 6, 2018, doi: 10.3991/ijet.v13i06.8442.
A. Nugroho, W. Priatna, and I. Romli, “Implementasi Algoritma Genetika untuk Optimasi Penjadwalan Mata Kuliah,” Jurnal Penelitian Teknik Informatika, vol. 1, no. 2, pp. 188–194, 2018.
A. Jain, S. Jain, and P. K. Chande, “Formulation of Genetic Algorithm to Generate Good Quality Course Timetable,” International Journal of Innovation, Management and Technology, vol. 1, no. 3, pp. 248–251, 2010.
A. S. Wicaksana, B. D. Setiawan, and B. Rahayudi, “Algoritma Genetika untuk Optimasi Fuzzy Time Series dalam Memprediksi Kepadatan Lalu Lintas di Jalan Tol,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 2, no. 3, pp. 1063–1071, 2018.
D. A. Suprayogi and W. F. Mahmudy, “Penerapan Algoritma Genetika Travelling Salesman Problem with Time Window: Studi Kasus Rute Antar Jemput Laundry,” Jurnal Buana Informatika, vol. 6, no. 2, pp. 121–130, 2015.
L. Paranduk, A. Indriani, M. Hafid, and Suprianto, “Sistem Informasi Penjadwalan Mata Kuliah Menggunakan Algoritma Berbasis Web,” Seminar Nasional Aplikasi Teknologi Informasi (SNATi), pp. E46–E50, 2018.
N. L. G. P. Suwirmayanti, I. M. Sudarsana, and S. Darmayasa, “Penerapan Algoritma Genetika Untuk Penjadwalan Mata Pelajaran,” Journal of Applied Intelligent System, vol. 1, no. 3, pp. 220–233, 2016.
S. A. Wicaksono, “Optimasi Sistem Penempatan Magang Menerapkan Algoritme Genetika,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 6, no. 1, p. 17, 2019, doi: 10.25126/jtiik.201961950.
D. Oktarina and A. Hajjah, “Perancangan Sistem Penjadwalan Seminar Proposal Dan Sidang Skripsi Dengan Metode Algoritma Genetika,” JOISIE Journal Of Information System And Informatics Engineering, vol. 3, no. 1, pp. 32–40, 2019.
D. Hermawanto, “Beberapa Metode Seleksi Algoritma Genetika | denny...,” May 11, 2007. https://dennyhermawanto.wordpress.com/2007/05/11/beberapa-metode-seleksi-algoritma-genetika/ (accessed Jun. 16, 2021).
A. K. Nugroho, “Image Quantization in Psoriasis Using K-Mean Clustering,” Conference SENATIK STT Adisutjipto Yogyakarta, vol. 4, 2018, doi: 10.28989/senatik.v4i0.162.
I. Permadi and A. K. Nugroho, “Klasifikasi Citra Menggunakan Kombinasi Jaringan Syaraf Tiruan Model Perceptron dan Algoritma One vs Rest,” INOVTEK Polbeng - Seri Informatika, vol. 4, no. 2, 2019, doi: 10.35314/isi.v4i2.1062.
Abstract viewed = 45 times
PDF downloaded = 43 times
Copyright (c) 2022 Arief Kelik Nugroho
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.