Penerapan Memetic Algorithm Untuk Optimasi Jadwal Perkuliahan dengan Mempertimbangkan Preferensi Dosen dan Mahasiswa

Authors

  • Nirwan Sinuhaji Institut Teknologi dan Bisnis Indonesia
  • Nurhafis Ahmad Rangkuti Institut Teknologi dan Bisnis Indonesia
  • Indah Mawati Giawa Institut Teknologi dan Bisnis Indonesia
  • Devita Ginting Institut Teknologi dan Bisnis Indonesia

DOI:

https://doi.org/10.58918/lofian.v6i1.297

Keywords:

Memetic Algorithm, Optimization, Lecture Scheduling, Genetic Algorithm, Constraint Satisfaction

Abstract

Class scheduling is a crucial aspect of higher education academic management, facing various constraints, such as classroom availability, lecturer teaching hours, classroom capacity, and student needs to ensure they attend courses without scheduling conflicts. Manual schedule creation is often time-consuming and prone to errors, especially as the number of courses, lecturers, and classrooms increases. Therefore, an optimization method capable of producing effective and efficient schedules is required. This study applies the Memetic Algorithm (MA) to solve the class schedule optimization problem. The Memetic Algorithm is a development of the Genetic Algorithm that combines population evolution with local search to improve solution quality. In this study, each solution is represented as a set of class schedules that must satisfy various hard and soft constraints. The optimization process involves population initialization, selection, crossover, mutation, and solution refinement using local search. The expected outcome of this research is the creation of a scheduling system capable of producing an optimal lecture schedule with minimal conflict, more effective space utilization, and efficient computing time. The application of the Memetic Algorithm is expected to be an alternative solution for managing academic scheduling in higher education.

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Author Biography

  • Devita Ginting, Institut Teknologi dan Bisnis Indonesia

    saya, Devita Permata Sari, M.Kom. merupakan dosen tetap di prodi Teknik Informatika, Fakultas sains dan teknologi, Institut Teknologi dan Bisnis Indonesia. Saat ini, saya memegang jabatan fungsional akademik sebagai Asisten Ahli. saya menyelesaikan studi magister di bidang Ilmu Komputer (teknik informatika) dengan fokus riset pada optimasi sistem, kecerdasan buatan, dan pengembangan perangkat lunak berbasis seluler. Selain aktif mengajar mata kuliah inti rumpun informatika, ia juga produktif dalam mempublikasikan artikel ilmiah di berbagai jurnal nasional maupun internasional yang terindeks di Sinta.

References

Nugroho, M. A., & Hermawan, G. (2018). Solving University Course Timetabling Problem Using Using Memetic Algorithms and Rule-Based Approaches. IOP Conference Series: Materials Science and Engineering

Burke, E. K., & Petrovic, S. (2002). Recent Research Directions in Automated Timetabling. European Journal of Operational Research, 140(2), 266–280. Referensi ini menjelaskan perkembangan penelitian penjadwalan otomatis serta berbagai pendekatan optimasi yang digunakan.

Cotta, C., & Fernández-Leiva, A. J. (2007). Memetic Algorithms in Planning, Scheduling, and Timetabling. In Evolutionary Scheduling (Studies in Computational Intelligence, Vol. 49). Springer

Alkan, A., & Özcan, E. (2003). Memetic Algorithms for Timetabling. Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2003). IEEE.

Ghaffar, A., Sattar, M. U., Munir, M., & Qureshi, Z. (2022). Multi-objective Fuzzy-based Adaptive Memetic Algorithm with Hyper-Heuristics to Solve University Course Timetabling Problem. EAI Endorsed Transactions on Scalable Information Systems,

Ghaffar, A., Sattar, M. U., Munir, M., & Qureshi, Z. (2022). Multi-objective Fuzzy-based Adaptive Memetic Algorithm with Hyper-Heuristics to Solve University Course Timetabling Problem. EAI Endorsed Transactions on Scalable Information Systems,

Burke, E. K., & Petrovic, S. (2002). Recent Research Directions in Automated Timetabling. European Journal of Operational Research, 140(2), 266–280. Referensi ini menjelaskan perkembangan penelitian penjadwalan otomatis serta berbagai pendekatan optimasi yang digunakan.

Michalewicz, Z. (1996). Genetic Algorithms + Data Structures = Evolution Programs (3rd ed.). Springer. Buku ini menjadi rujukan penting dalam memahami Genetic Algorithm yang merupakan dasar dari Memetic Algorithm.

Moscato, P. (1989). On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts: Towards Memetic Algorithms. California Institute of Technology. Karya ini merupakan publikasi awal yang memperkenalkan kocnsep Memetic Algorithm dan menjadi referensi fundamental dalam bidang tersebut.

Sivanandam, S. N., & Deepa, S. N. (2008). Introduction to Genetic Algorithms. Springer. Buku ini membahas konsep Genetic Algorithm beserta implementasinya sebagai dasar sebelum mempelajari Memetic Algorithm.

Blum, C., & Roli, A. (2003). Metaheuristics in Combinatorial Optimization: Overview and Conceptual Comparison. ACM Computing Surveys, 35(3), 268–308.

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Published

2026-07-29

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Section

Articles

How to Cite

Penerapan Memetic Algorithm Untuk Optimasi Jadwal Perkuliahan dengan Mempertimbangkan Preferensi Dosen dan Mahasiswa. (2026). LOFIAN: Jurnal Teknologi Informasi Dan Komunikasi, 6(1), 1-7. https://doi.org/10.58918/lofian.v6i1.297