Implementation of Genetic Algorithm for Subject Scheduling at SD Taman Cahya Pematangsiantar

Authors

  • Muhammad Irfan STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Muhammad Ridwan Lubis STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Zulaini Masruro Nasution STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

DOI:

https://doi.org/10.55123/jomlai.v1i2.940

Keywords:

Genetic Algorithm, Scheduling, Subjects, Primary School, Pematangsiantar

Abstract

The teaching schedule in schools is essential in teaching and learning activities; this schedule aims to support, facilitate, and improve the quality of education. With a teaching schedule, teaching and learning activities will run smoothly and efficiently. Until now, the scheduling of lessons in several schools is still done conventionally by the curriculum department, with previously held meetings for the division of tasks with the supervising teacher. The conventional teaching scheduling system for school teachers will be deemed less effective. In addition to requiring very high accuracy and relatively few estimates, this method also allows for errors. Therefore, this study aims to implement a genetic algorithm to optimize subject scheduling and apply the teacher scheduling model generated by the genetic algorithm in a web application. The data of this study were collected from observations at SD Taman Cahya Pematangsiantar. As a result, scheduling using genetic algorithms can generate schedules automatically, displaying the plan on the day and hour of each teacher's teaching schedule, thus creating an optimal solution for scheduling. In addition, applying the Genetic Algorithm is faster and easier in the process of making a schedule for setting teacher teaching hours so that it does not take a long time.

References

S. N. Abu, “Pembinaan guru oleh kepala sekolah dalam pengelolaan pembelajaran di sekolah dasar,” Jurnal Bahana Manajemen Pendidikan, vol. 2, no. 1, pp. 704–831, 2014.

N. K. S. Astini, “Pemanfaatan Teknologi Informasi dalam Pembelajaran Tingkat Sekolah Dasar pada Masa Pandemi Covid-19,” Jurnal Lembaga Penjaminan Mutu STKIP Agama Hindu Amlapura, vol. 11, no. 2, pp. 13–25, 2020.

D. Permana, I. Kudsi, M. Salam, Y. Iriantara, and U. C. Barlian, “Inovasi Pembelajaran dengan Model Blended learning di Masa Pandemi Covid 19,” VOCATIONAL: Jurnal Inovasi Pendidikan Kejuruan, vol. 1, no. 1, pp. 31–47, 2021.

N. Gustini and Wulandari, “Manajemen Laboratorium Sains untuk Meningkatkan Mutu Pembelajaran,” Jurnal Islamic Education Manajemen, vol. 5, no. 2, pp. 231–244, 2020.

S. Wibowo, “Penerapan Logika Fuzzy Dalam Penjadwalan Waktu Kuliah,” Jurnal Informatika UPGRIS, vol. 1, no. 1, pp. 59–77, 2015.

A. Wanto and E. Kurniawan, “Seleksi Penerimaan Asisten Laboratorium Menggunakan Algoritma AHP Pada AMIK-STIKOM Tunas Bangsa Pematangsiantar,” Jurnal Informatika dan Komputer (JIKO), vol. 3, no. 1, pp. 11–18, 2018.

V. V. Sianipar, A. Wanto, and M. Safii, “Decision Support System for Determination of Village Fund Allocation Using AHP Method,” The IJICS (International Journal of Informatics and Computer Science) ISSN, vol. 4, no. 1, pp. 20–28, 2020.

P. P. P. A. N. . F. I. R.H Zer, Masitha, A. P. Windarto, and A. Wanto, “Analysis of the ELECTRE Method on the Selection of Student Creativity Program Proposals,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, Aug. 2019.

D. M. Sinaga, R. R, R. Alfah, A. P. Windarto, and A. Wanto, “Jurnal Sains dan Informatika,” Jurnal Sains dan Informatika, vol. 5, no. 2, pp. 129–135, 2018.

D. R. Sari, N. Rofiqo, D. Hartama, A. P. Windarto, and A. Wanto, “Analysis of the Factors Causing Lazy Students to Study Using the ELECTRE II Algorithm,” Journal of Physics: Conference Series, vol. 1255, no. 1, p. 012007, Aug. 2019.

T. Imandasari, A. Wanto, and A. P. Windarto, “Analisis Pengambilan Keputusan Dalam Menentukan Mahasiswa PKL Menggunakan Metode PROMETHEE,” Jurnal Riset Komputer (JURIKOM), vol. 5, no. 3, pp. 234–239, 2018.

R. Watrianthos, W. A. Ritonga, A. Rengganis, A. Wanto, and M. Isa Indrawan, “Implementation of PROMETHEE-GAIA Method for Lecturer Performance Evaluation,” Journal of Physics: Conference Series, vol. 1933, no. 1, p. 012067, 2021.

G. W. Bhawika et al., “Implementation of ANN for Predicting the Percentage of Illiteracy in Indonesia by Age Group,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

A. Wanto et al., “Analysis of the Backpropagation Algorithm in Viewing Import Value Development Levels Based on Main Country of Origin,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

E. Siregar, H. Mawengkang, E. B. Nababan, and A. Wanto, “Analysis of Backpropagation Method with Sigmoid Bipolar and Linear Function in Prediction of Population Growth,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

M. K. Z. Sormin, P. Sihombing, A. Amalia, A. Wanto, D. Hartama, and D. M. Chan, “Predictions of World Population Life Expectancy Using Cyclical Order Weight / Bias,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

A. Wanto et al., “Analysis of the Accuracy Batch Training Method in Viewing Indonesian Fisheries Cultivation Company Development,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

Y. Andriani, H. Silitonga, and A. Wanto, “Analisis Jaringan Syaraf Tiruan untuk prediksi volume ekspor dan impor migas di Indonesia,” Register: Jurnal Ilmiah Teknologi Sistem Informasi, vol. 4, no. 1, pp. 30–40, 2018.

W. Saputra, J. T. Hardinata, and A. Wanto, “Implementation of Resilient Methods to Predict Open Unemployment in Indonesia According to Higher Education Completed,” JITE (Journal of Informatics and Telecommunication Engineering), vol. 3, no. 1, pp. 163–174, 2019.

N. L. W. S. R. Ginantra et al., “Performance One-step secant Training Method for Forecasting Cases,” Journal of Physics: Conference Series, vol. 1933, no. 1, pp. 1–8, 2021.

N. Arminarahmah, A. D. GS, G. W. Bhawika, M. P. Dewi, and A. Wanto, “Mapping the Spread of Covid-19 in Asia Using Data Mining X-Means Algorithms,” IOP Conf. Series: Materials Science and Engineering, vol. 1071, no. 1, p. 012018, 2021.

A. Pradipta, D. Hartama, A. Wanto, S. Saifullah, and J. Jalaluddin, “The Application of Data Mining in Determining Timely Graduation Using the C45 Algorithm,” IJISTECH (International Journal of Information System & Technology), vol. 3, no. 1, pp. 31–36, 2019.

T. H. Sinaga, A. Wanto, I. Gunawan, S. Sumarno, and Z. M. Nasution, “Implementation of Data Mining Using C4.5 Algorithm on Customer Satisfaction in Tirta Lihou PDAM,” Journal of Computer Networks, Architecture, and High-Performance Computing, vol. 3, no. 1, pp. 9–20, 2021.

N. A. Febriyati, A. D. GS, and A. Wanto, “GRDP Growth Rate Clustering in Surabaya City uses the K- Means Algorithm,” International Journal of Information System & Technology, vol. 3, no. 2, pp. 276–283, 2020.

J. Hutagalung, N. L. W. S. R. Ginantra, G. W. Bhawika, W. G. S. Parwita, A. Wanto, and P. D. Panjaitan, “COVID-19 Cases and Deaths in Southeast Asia Clustering using K-Means Algorithm,” Journal of Physics: Conference Series, vol. 1783, no. 1, p. 012027, 2021.

I. Parlina et al., “Naive Bayes Algorithm Analysis to Determine the Percentage Level of visitors the Most Dominant Zoo Visit by Age Category,” in Journal of Physics: Conference Series, 2019, vol. 1255, no. 1, p. 012031.

M. A. Hanafiah and A. Wanto, “Implementation of Data Mining Algorithms for Grouping Poverty Lines by District/City in North Sumatra,” International Journal of Information System & Technology, vol. 3, no. 2, pp. 315–322, 2020.

I. S. Damanik, A. P. Windarto, A. Wanto, Poningsih, S. R. Andani, and W. Saputra, “Decision Tree Optimization in C4.5 Algorithm Using Genetic Algorithm,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–7, 2019.

A. Wanto et al., Data Mining : Algoritma dan Implementasi. Yayasan Kita Menulis, 2020.

D. Hartama, A. Perdana Windarto, and A. Wanto, “The Application of Data Mining in Determining Patterns of Interest of High School Graduates,” Journal of Physics: Conference Series, vol. 1339, no. 1, p. 012042, Dec. 2019.

M. Yazdani, B. Naderi, and E. Zeinali, “Algorithms for University Course Scheduling Problems,” Tehnicki Vjesnik, vol. 24, no. 2, pp. 241–247, 2017.

Ginting and W. Clarisa, “Implementasi Algoritma Genetika dalam Penjadwalan Shift Kerja di Call Center Telkomsel,” 2017.

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Published

2022-09-26

How to Cite

Irfan, M., Lubis, M. R., & Nasution, Z. M. (2022). Implementation of Genetic Algorithm for Subject Scheduling at SD Taman Cahya Pematangsiantar. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(2), 151–158. https://doi.org/10.55123/jomlai.v1i2.940

Issue

Vol. 1 No. 2 (2022): June

Section

Articles

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Copyright (c) 2022 Muhammad Irfan, Muhammad Ridwan Lubis, Zulaini Masruro Nasution

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