Scheduling System for Proposal Seminars and Final Project Examination Using Genetic Algorithms for Final Project Information Systems
DOI:
https://doi.org/10.33795/jartel.v16i2.9568Keywords:
Schedule, Scheduling System, Genetics Algorithm, Laravel, Proposal Seminars, Scheduling OptimizationAbstract
The process of scheduling seminar proposals and final project examination in academic environments often faces highly complex obstacles, such as lecturer schedule conflicts, room limitations, and difficulties in matching the expertise of examiners with the topics of students' final projects. This study aims to develop a web-based automatic scheduling system using genetic algorithms to optimize the allocation of lecturer, room, and time resources. The system was developed using the Laravel framework, where the genetic algorithm was used as a solution search engine through truncation selection, one-point crossover, and random resetting mutation mechanisms. Based on a series of parameter tests, the optimal algorithm configuration was obtained at a population size of 150, a maximum generation of 300, a crossover rate of 0.8, and a mutation rate of 0.01. The system implementation proved capable of generating valid schedule solutions without violating constraints (fitness 0) with high computational time efficiency. In a maximum workload scenario of 50 proposals, the system was able to compile a schedule in an average time of 2.717 seconds.
References
A.P.S. Iskandar, “Optimasi Penjadwalan Ujian Tugas Akhir Dengan Menggunakan Algoritma Genetika (Final Project Scheduling Optimization Using Genetic Algorithm),” J-COSINE, vol. 5, no. 1, pp. 40–48, Jun. 2021, [Online]. Available: http://jcosine.if.unram.ac.id/
Y. Bastian, D. J. Surjawan, and A. Adelia, “Aplikasi Penjadwalan Sidang di Fakultas Teknologi Informasi UK Maranatha,” Jurnal Teknik Informatika dan Sistem Informasi, vol. 4, no. 1, Apr. 2018, doi: 10.28932/jutisi.v4i1.760.
S. Eka Putri and N. Napitupulu, “Implementation and Analysis of Depth-First Search (DFS) Algorithm for Finding The Longest Path,” the International Seminar on Operational Research (InteriOR), Medan, Indonesia, Aug. 2011, doi: 10.13140/2.1.2878.2721
L. A. Pangestu, S. H. Suryawan, and A. J. Latipah, “Penerapan Algoritma Genetika Dalam Penjadwalan Mata Pelajaran,” Jurnal Informatika, vol. 10, no. 2, pp. 194–205, Oct. 2023, doi: 10.31294/inf.v10i2.16701.
T. Kristian Jeriko, D. Faizal Racma, C. Ety Widjayanti, and A. Ary Setyawan, “Penerapan Algoritma Genetika Dalam Sistem Informasi Penjadwalan Mata Kuliah Berbasis Website Pada STIKOM Yos Sudarso Purwokerto,” vol. 6, no. 1, pp. 101–118, 2022, doi: 10.24912/jmstkik.v6i1.17262.
D. Wahyuningsih and E. Helmud, “Penerapan Algoritma Genetika Untuk Optimasi Penjadwalan pada MTS Negeri 1 Pangkalpinang,” Jurnal Sisfokom (Sistem Informasi dan Komputer), vol. 9, no. 3, pp. 435–441, Dec. 2020, doi: 10.32736/sisfokom.v9i3.994.
L. Aga Aditya and W. P. Mega, “Implementasi Algoritma Genetika Untuk Penjadwalan Mata Pelajaran Pada LMS Getsmart,” 2017. [Online]. Available: http://putranugraha.id.
M. Fauzi, Z. Akbar, and K. Kurniawansyah, “Sistem Penjadwalan Sidang Skripsi Dengan Algoritma Genetika Pada Program Studi Informatika Universitas Muhammadiyah Jambi,” Jurnal Informatika, Sistem Informasi dan Kehutanan (FORSINTA), vol. 3, no. 2, 2024.
Rangga Gelar Guntara, M. Rizki Nugraha, Y. Prasetyo, and R. Aprilia, “Implementasi Algoritma Genetika Untuk Aplikasi Penjadwalan Sidang Tugas Akhir Berbasis Web,” Jurnal Minfo Polgan, vol. 12, no. 2, pp. 2224–2232, Nov. 2023, doi: 10.33395/jmp.v12i2.13206.
D. Yunda and S. Sari, “Sistem Informasi Tugas Akhir Berbasis Web di Jurusan Teknik Informatika Universitas Trisakti,” vol. 2, pp. 73–86.
S. D. Immanuel and U. Kr. Chakraborty, “Genetic Algorithm: An Approach on Optimization,” in 2019 International Conference on Communication and Electronics Systems (ICCES), 2019, pp. 701–708. doi: 10.1109/ICCES45898.2019.9002372.
A. Mauko, A. Fanggidae, and Y. Polly, “Analysis Of Elitism In Genetic Algorithm Using Ordinal Representation Coding On Traveling Salesman Problems,” J-Icon : Jurnal Komputer dan Informatika, vol. 10, no. 2, Dec. 2022, doi: 10.35508/jicon.v10i2.8473.
Q. Zhang, “An optimized solution to the course scheduling problem in universities under an improved genetic algorithm,” Journal of Intelligent Systems, vol. 31, no. 1, pp. 1065–1073, 2022, doi: doi:10.1515/jisys-2022-0114.
A. M. Fajrin, “Analisis Performa Dari One-Point, Multi-Point Dan Order Crossover Di Algoritma Genetika,” semanTIK, vol. 7, no. 2, pp. 1–5, 2021, doi: 10.5281/zenodo.5793087.
R. Kumar, M. Memoria, A. Gupta, and M. Awasthi, “Critical Analysis of Genetic Algorithm under Crossover and Mutation Rate,” in 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), 2021, pp. 976–980. doi: 10.1109/ICAC3N53548.2021.9725640.
