Searching for the Nearest Places of Worship in Bengkulu City Using Ant Colony Optimisation Algorithm
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Abstract
As a country with a population that has various religions, including Islam, Christianity, Buddhism and Hinduism, Indonesia also has many places of worship spread throughout the region. Bengkulu is an area visited by many tourists, both local and foreign. Therefore, public facilities in Bengkulu are very necessary, one of the facilities needed is a place of worship. Information about places of worship is important and needed by tourists, especially information about the nearest route that can be taken to the place of worship. This research was carried out in order to build a system that can provide information on the nearest places of worship as well as directions that can be used as a guide to that location by implementing the Ant Colony Optimization Algorithm to find the nearest route. This application, which was created using the PHP programming language and MySQL database, can be used with various devices because this application is website-based. The application of the Ant Colony Optimization algorithm produces a route that has the shortest distance to the location of the place of worship.
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[2] A. Zarman, M. Irfan, and W. Uriawan, “Implementasi Algoritma Ant Colony Optimization pada Aplikasi Pencarian Lokasi Tempat Ibadah Terdekat di Kota Bandung,” J. Online Inform., vol. 1, no. 1, p. 6, 2016, doi: 10.15575/join.v1i1.4.
[3] M. Dorigo and L. M. Gambardella, “Ant colony system: A cooperative learning approach to the traveling salesman problem,” IEEE Trans. Evol. Comput., vol. 1, no. 1, pp. 53–66, 1997, doi: 10.1109/4235.585892.
[4] A. Gusmão and S. H. Pramono, “Sistem Informasi Geografis Pariwisata Berbasis Web Dan Pencarian Jalur Terpendek Dengan Algoritma Dijkstra,” vol. 7, no. 2, pp. 125–130, 2013.
[5] A. Hidayat, I. Purnamasari, and D. M. Siringoringo, “Penentuan Jalur Terpendek dengan Metode Heuristik Menggunakan Algoritma Sarang Semut (Ant Colony) (Studi Kasus: Jalan Arteri Sekunder Kota Samarinda) Determination of the Shortest Path with the Heuristic Method Using the Ant Colony Algorithm (Case Study: ,” J. EKSPONENSIAL, vol. 11, no. 1, pp. 93–98, 2020.
[6] S. H. Ok, W. J. Seo, J. H. Ahn, S. Kang, and B. Moon, “An ant colony optimization approach for the preference-based shortest path search,” J. Chinese Inst. Eng. Trans. Chinese Inst. Eng. A, vol. 34, no. 2, pp. 181–196, 2011, doi: 10.1080/02533839.2011.565574.
[7] A. P. Wibowo and A. Ilyas, “Integrasi Algoritma Ant Colony Pada Pencarian Lokasi,” Ic-Tech, vol. 13, no. 2, pp. 43–48, 2018, [Online]. Available: http://ejournal.stmik-wp.ac.id
[8] B. lutfi A. Rofiq, H. Februariyanti, J. S. Wibowo, and Z. Budiarso, “Pencarian Tempat Ibadah Terdekat Menggunakan Algoritma Dijkstra,” JUSIM (Jurnal Sist. Inf. Musirawas), vol. 6, no. 1, pp. 19–28, 2021, doi: 10.32767/jusim.v6i1.1138.
[9] S. Fernandez, C. Prihantoro, and A. K. Hidayah, “Implementasi Weighted Product Pada Pemilihan Dosen Terbaik di Universitas Muhammadiyah Bengkulu,” J. Pseudocode, vol. VIII, no. 2, pp. 126–133, 2021.
[10] A. Gupta and S. Srivastava, “Comparative Analysis of Ant Colony and Particle Swarm Optimization Algorithms for Distance Optimization,” Procedia Comput. Sci., vol. 173, no. 2019, pp. 245–253, 2020, doi: 10.1016/j.procs.2020.06.029.