PENJADWALAN MATA KULIAH DENGAN ALGORITMA PARTICLE SWARM OPTIMIZATION

• Main Author: Athiyah Rizqillah Adzhari, - (Author)
• Format: Book
• Published: 2020-08-26.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Link Metadata
• Notes: http://repository.upi.edu/51423/1/S_MAT_1606265_Title.pdf; http://repository.upi.edu/51423/2/S_MAT_1606265_Chapter1.pdf; http://repository.upi.edu/51423/3/S_MAT_1606265_Chapter2.pdf; http://repository.upi.edu/51423/4/S_MAT_1606265_Chapter3.pdf; http://repository.upi.edu/51423/5/S_MAT_1606265_Chapter4.pdf; http://repository.upi.edu/51423/6/S_MAT_1606265_Chapter5.pdf; http://repository.upi.edu/51423/7/S_MAT_1606265_Appendix.pdf
• Keywords: L Education (General); QA Mathematics

ABSTRAK Penelitian ini membahas masalah penjadwalan mata kuliah di departemen pendidikan matematika FPMIPA Universitas Pendidikan Indonesia. Penjadwalan mata kuliah termasuk ke dalam jenis timetabling yang digolongkan sebagai NP-Hard Problem (Nondeterministic Polynomial Time). Oleh karena itu diperlukan suatu metode untuk menyelesaikan masalah penjadwalan mata kuliah. Pada penelitian ini digunakan algoritma Particle Swarm Optimization untuk menyelesaikan masalah penjadwalan mata kuliah di Departemen Pendidikan Matematika FPMIPA Universitas Pendidikan Indonesia. Algoritma Particle Swarm Optimization merupakan algoritma berbasis populasi yang mengeksploitasi partikel dalam pencarian. Hasil implementasi menunjukkan bahwa algoritma Particle Swarm Optimization dapat diimplementasikan untuk masalah penjadwalan mata kuliah di Departemen Pendidikan Matematika FPMIPA Universitas Pendidikan Indonesia. Kata Kunci: Penjadwalan, Algoritma Particle Swarm Optimization, Model Optimisasi, Solusi Optimal. ABSTRACT This research disscuss about a lecture timetabling problem at Department of Mathematics Education, Faculty of Mathematics and Science Education, Indonesia. The problem is classified as NP-Hard Problem (Nondeterministic Polynomial Time). Therefore, we need a method to solve the lecture timetabling problem. In this research, we use particle swarm optimization algorithm to solve the problem. The algorithm is a population-based that uses particles searching. The computational result shows that the particle swarm optimization algorithm can be implemented for lecture timetabling problem at Department of Mathematics Education, Faculty of Mathematics and Science Education, Indonesia University of Education. Keyword: Timetabling, Particle Swarm Optimization Algorithm, Optimization Model, Optimal Solution.