Penerapan Algoritma Genetika Untuk Optimasi Penjadwalan pada MTS Negeri 1 Pangkalpinang

Authors

DOI:

https://doi.org/10.32736/sisfokom.v9i3.994

Keywords:

Scheduling, MTS Negeri 1 Pangkalpinang, Genetic Algorithm

Abstract

Scheduling is a very important thing to do at school. The schedule, which is still being carried out manually at MTS Negeri 1 Pangkalpinang, requires time to manage teacher slots, classes, subjects, and times where in MTS teacher hours have been determined by the department of religion so that it takes quite a long time to process the formation of the schedule. This study aims to utilize genetic algorithms in optimizing scheduling in a short time. The genetic algorithm is an algorithm that is effective in dealing with scheduling. The results of data testing were carried out with 15, 20, 25 and 30 subjects. Testing with 15 subjects took 19.56 seconds to form a schedule and there were no conflicting schedules, while with 20 data subjects the time to process the schedule formation took 42.15 seconds, 25 data with 94.07 seconds and 30 data with time 471.60. The average time required to process the data is 156.845 seconds.

Author Biographies

Delpiah Wahyuningsih, ISB Atma Luhur

Teknik Informatika

Ellya Helmud, ISB Atma Luhur

Sistem Informasi

References

A. T. Ma’arif and D. P. Pamungkas, “Penerapan Metode Algoritma Genetika untuk Optimasi Penjadwalan Mata Kuliah,” Semin. Nas. Inov. Teknol. UN PGRI Kediri, pp. 93–97, 2018.

S. Ni Luh Gede Pivin, S. I Made, and D. Suta, “Penerapan Algoritma Genetika Untuk Penjadwalan Mata Pelajaran,” J. Appl. Intell. Syst., vol. 1, no. 3, pp. 220–233, 2016.

D. Oktarina and A. Hajjah, “Perancangan Sistem Penjadwalan Seminar Proposal dan Sidang Skripsi dengan Metode Algoritma Genetika,” JOISIE (Journal Inf. Syst. Informatics Eng., vol. 3, no. 1, p. 32, 2019, doi: 10.35145/joisie.v3i1.421.

A. Hajjah, “Penerapan Algoritma Genetika dalam Optimasi Penjadwalan Proyek,” vol. 2, no. 1, pp. 50–55, 2020.

A. Josi, “Implementasi Algoritma Genetika Pada Aplikasi Penjadwalan Perkuliahan Berbasis Web Dengan Mengadopsi Model Waterfall,” J. Inform. J. Pengemb. IT, vol. 02, no. 02, pp. 77–83, 2017, doi: 10.30591/JPIT.V2I2.517.G554.

Y. Elva, “Sistem Penjadwalan Mata Pelajaran Menggunakan Algoritma Genetika,” J. Teknol. Inf., vol. 3, no. 1, p. 49, 2019, doi: 10.36294/jurti.v3i1.687.

R. M. Puspita, A. Arini, and S. U. Masrurah, “Pengembangan Aplikasi Penjadwalan Kegiatan Pelatihan Teknologi Informasi Dan Komunikasi Dengan Algoritma Genetika (Studi Kasus: Bprtik),” J. Online Inform., vol. 1, no. 2, pp. 76–81, 2016, doi: 10.15575/join.v1i2.43.

Monalisa and Diana, “OPTIMASI PENJADWALAN SHIFT KERJA MENERAPKAN ALGORITMA GENETIK,” Bina Darma Conf. Comput. Sci., no. Vol 2 No 2 (2020): Bina Darma Conference on Computer Science (BDCCS), pp. 453–460, 2020, [Online]. Available: http://conference.binadarma.ac.id/index.php/BDCCS/article/view/1318.

A. Nugroho, W. Priatna, and I. Romli, “Implementasi Algoritma Genetika Untuk Optimasi Penjadwalan Mata Kuliah,” J. Teknol. dan Ilmu Komput. Prima, vol. 1, no. 2, pp. 35–41, 2018, doi: 10.34012/jutikomp.v1i2.238.

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Published

2020-12-03

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