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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika
I Gusti Agung Premananda
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Computer Science & IT Control & Systems Engineering

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Optimasi Penjadwalan Mata Kuliah Menggunakan Algoritma Late Acceptence Hill Climbing Berbasis Hiper Heuristik I Gusti Agung Premananda; Ahmad Muklason
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 8 No 2 (2021): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v8i2.778

Abstract

Course scheduling is one area of ​​operations research. This problem schedules a class without violating an existing constraint. At this time the problem of scheduling courses is becoming increasingly complex with existing limitations One of them is in International Timetabling Competition 2019 (ITC 2019) which released the latest real world dataset. This study focuses on optimizing the quality of course scheduling in order to reduce the value of the final solution of course scheduling. The algorithm used is Late Acceptance Hill Climbing (LAHC) with a hyper-heuristic approach using mutation Low Level Heuristics (LLH) and local search. The algorithm was applied to 30 ITC 2019 data sets with 100,000 iterations in 5 trials. The result is that the application of this algorithm is able to optimize with an average of 52% of the initial solution. In addition, this algorithm produces a consistent solution for 10 attempts on each dataset.
Automated Course Timetabling Optimization Using Tabu-Simulated Annealing Hyper-Heuristics Algorithm Ahmad Muklason; Ahsanul Marom; I Gusti Agung Premananda
Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika Vol. 10 No. 1 (2024): April 2024
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v10i1.4835

Abstract

The topic of solving Timetabling Problems is an interesting area of study. These problems are commonly encountered in many institutions, particularly in the educational sector, including universities. One of the challenges faced by universities is the Course Timetabling Problem, which needs to be addressed regularly in every semester, taking into consideration the available resources. Solving this problem requires a significant amount of time and resources to create the optimal schedule that adheres to the predefined constraints, including both hard and soft constraints. As a problem of computational complexity, University Course Timetabling is NP-hard, meaning that there are no exact conventional algorithms that can solve it in polynomial time. Several methods and algorithms have been proposed to optimize course timetabling in order to achieve the optimal results. In this study, a new hybrid algorithm based on Hyper-Heuristics is developed to solve the course timetabling problem using the Socha Dataset. This algorithm combines the strengths of Simulated Annealing and Tabu Search to balance the exploitation and exploration phases and streamline the search process. The results show that the developed algorithm is competitive, ranking second out of ten previous algorithms, and finding the best solution in six datasets.
Co-Authors Ahmad Muklason Ahsanul Marom