Web-Based Internship Scheduling System for Imelda Medan Vocational High School of Tourism Students Using the Ant Colony Optimization (ACO) Method
##plugins.themes.bootstrap3.article.main##
Abstract
Field Work Practice (PKL) is an important component of vocational education that provides students with real workplace experience. However, scheduling PKL activities often encounters problems such as overlapping schedules, mismatched student quotas, and inefficient time management. At Imelda Medan Vocational High School of Tourism, the scheduling process is still done manually, which often leads to errors and delays. This study proposes a web-based PKL scheduling system using the Ant Colony Optimization (ACO) method to generate optimal and efficient schedules. The ACO algorithm imitates the behavior of ants in finding the shortest path, making it suitable for solving complex scheduling problems. The system is expected to minimize schedule conflicts, balance student placement, and simplify data management for schools, students, and partner industries.
##plugins.themes.bootstrap3.article.details##
[2] Model Penerapan Algoritma Ant Colony Optimization (ACO) untuk Optimasi Sistem Informasi Penjadwalan Kuliah, Sidik, R., Fitriawati, M., Mauluddin, S., & Nursikuwagus, A. (2018). Jurnal Teknologi dan Informasi (JATI), 8(2), 120-132.
[3] Chandra, B., & Kumar, S. (2020). Application of Ant Colony Optimization Algorithm in Task Scheduling for Cloud Computing Environment. International Journal of Computer Applications, 176(4), 1–7.
[4] Tarek, A., & Hassan, R. (2020). Comparative Study of Metaheuristic Algorithms for Scheduling Problems: Focus on Ant Colony Optimization. Procedia Computer Science, 170, 123–130.
[5] Siyamtining Tyas, E., & Prijodiprodjo, B. (2023). Implementation of Ant Colony Optimization for Scheduling Problems. Journal of Applied Informatics, 5(2), 45–53.
[6] Imelda Medan Vocational High School of Tourism. (2020). Internship Implementation Guidelines (Field Work Practice). Medan: School Publication.
[7] Rachmawati, I., & Prasetyo, D. (2020). Design of Web-Based Academic Scheduling Information System Using PHP and MySQL. Journal of Information Systems Research, 12(3), 211–219.
[8] Singh, A., & Kaur, M. (2020). Hybrid Ant Colony Optimization for Efficient Scheduling and Resource Allocation. Journal of Intelligent Systems, 29(1), 45–59.
[9] Dorigo, M., & Stützle, T. (2020). Ant Colony Optimization: Overview and Recent Advances. Springer Nature.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.