Sistem Penjadwalan Sidang Tugas Akhir menggunakan Algoritma Genetika
Abstract
Objective this research is to automatically schedule student final assignments using genetic algorithms in the Automation Engineering Technology Study Program of the Manufacturing Polytechnic in Bandung. Genetic Algorithm (GA) is a heuristic method or a method of finding optimal values using the principles of evolution. GA is used as a solution search algorithm in this research. The solution was implemented into a program that can create a schedule automatically based on the limitations set by program users. Scheduling parameters that are focused on in this study are duplication or clash issues and category suitability between the final project and examiners. Based on these parameters the program can produce the optimal schedule with varying success rates depending on the ratio between the number of trial examiners and the number of examiners needed at one time, where a ratio above 2: 1 result in success above 90% for duplication cases, and the ratio is above 1.5: 1 for category conformance cases.
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Abdullah, S., & Turabieh, H. (2008). Generating university course timetable using Genetic Algorithms and local search. Proceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008, 1(November), 254–260. https://doi.org/10.1109/ICCIT.2008.379
Bulman, M. (2017). SDLC - Waterfall Model. The Independent, May.
Ferawaty, E. (2010). Optimasi Penjadwalan Mata Kuliah pada Perguruan Tinggi dengan Menggunakan Algoritma Genetika.
Fiarni, C., Gunawan, A. S., Ricky, Maharani, H., & Kurniawan, H. (2015). Automated Scheduling System for Thesis and Project Presentation Using Forward Chaining Method with Dynamic Allocation Resources. Procedia Computer Science, 72, 209–216. https://doi.org/10.1016/j.procs.2015.12.133
Mawaddah, N. K., & Mahmudy, W. F. (2006). Optimasi Penjadwalan Ujian menggunakan Algoritma Genetika. Kursor, 2(2), 1–8. wayanfm@ub.ac.id
Permadi, I. (2010). Penerapan Algoritma Genetika untuk Optimasi Penjadwalan Tebangan Hutan (Applying of Genetic Algorithm for Scheduling Optimation Cuts Away Forest). Juita, 1, 19–27.
Pinedo, M. L. (2016). Scheduling Theory, Algorithm and Systems (5th ed.). Springer. https://doi.org/10.1007
Robandi, I. (2019). Artificial Intelligence - Mengupas Rekayasa Kecerdasan Tiruan (M. Kika (ed.); 1st ed.). ANDI.
Sari, Y., Alkaff, M., Wijaya, E. S., Soraya, S., & Kartikasari, D. P. (2019). Optimasi Penjadwalan Mata Kuliah Menggunakan Metode Algoritma Genetika dengan Teknik Tournament Selection. Jurnal Teknologi Informasi Dan Ilmu Komputer, 6(1), 85. https://doi.org/10.25126/jtiik.2019611262
Zukhri, Z. (2014). ALGORITMA GENETIKA, Metode Komputasi Evolusioner untuk Menyelesaikan Masalah Optimasi (Seno (ed.); 1st ed.). ANDI.
DOI: https://doi.org/10.31884/jtt.v7i1.310
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