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Comparison Analysis of Graph Theory Algorithms for Shortest Path Problem Riti, Yosefina Finsensia; Iskandar, Jonathan Steven; Hendra, Hendra
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1756

Abstract

The Sumba region, Indonesia, is known for its extraordinary natural beauty and unique cultural richness. There are 19 interesting tourist attractions spread throughout the area, but tourists often face difficulties in planning efficient visiting routes. From this case, it can be solved by applying graph theory in terms of searching for the shortest distance which is completed using the shortest path search algorithm. Then these 19 tourist objects are used to build a weighted graph, where the nodes represent the tourist objects and the edges of the graph describe the distance or travel time between these objects. Therefore, this research aims to compare the shortest path search algorithm with parameters to compare the shortest distance results, algorithm complexity and execution time for tourism in the Sumba area. The results of this research involve a comparison of several shortest path search algorithms, with the aim of finding the shortest distance results, algorithm complexity, and execution time for tourism in the Sumba area. Based on the test results of the five algorithms with the parameters that have been prepared, and the findings show that each algorithm has its own characteristics, the results are as follows: Dijkstra's algorithm can be used to calculate the shortest route for single-source and single-destination types. This resembles the Bellman-Ford algorithm, only the Bellman-Ford algorithm can be used simultaneously on graphs that have negative weight values. Meanwhile, the Floyd-Warshall algorithm is suitable for use on the all-pairs type. Then, the Johnson Algorithm can be used to determine the shortest path from all pairs of paths where the destination node is located in the graph. Finally, the Ant Colony algorithm to compute from a node to each pair of destination nodes.
Perbandingan Algoritma Greedy dan Algoritma Dijkstra dalam Pencarian Rute Terpendek dari Kabupaten Tuban ke Kota Surabaya Iskandar, Jonathan Steven; Riti, Yosefina Finsensia
Petik: Jurnal Pendidikan Teknologi Informasi Dan Komunikasi Vol. 8 No. 2 (2022): Volume 8 No 2 Tahun 2022
Publisher : Pendidikan Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/petik.v8i2.1255

Abstract

Abstrak — Menemukan jarak terpendek adalah masalah umum bagi pengguna transportasi dari awal. Hal ini dikarenakan para pengguna transportasi membutuhkan jarak yang pendek dan waktu yang singkat agar dapat mencapai perjalanan dengan cepat. Masalah transportasi sering muncul dari lokasi terpencil, terutama jika ada pengguna transportasi mencoba untuk pergi ke kota besar. Telah banyak algoritma yang digunakan untuk membantu menemukan rute terpendek dari satu kota ke kota lain diantaranya algoritma Greedy dan algoritma Dijkstra. Pada penelitian ini diimplementasi kedua algoritma tersebut untuk mencari jalur terpendek dengan cakupan wilayah dari Kabupaten Tuban (sebagai vertex T) hingga ke Kota Surabaya (sebagai vertex S). Kedua algoritma yang digunakan dibandingkan dengan menggunakan 4 (empat) parameter yaitu (1)waktu algoritma, (2) kompleksitas algoritma, (3) urutan pemrograman algoritma, dan (4) hasil jarak yang ditempuh saat menyelesaikan algoritma. Dari hasil perbandingan dapat disimpulkan bahwa algoritma Greedy lebih unggul terkait waktu eksekusi, kompleksitas, dan urutan algoritma, namun untuk hasil rute terpendek algoritma Dijkstra lebih unggul dibandingkan dengan algoritma Greedy dengan rute terpendek yang dihasilkan 105 Km, sedangkan algoritma Greedy menghasilkan rute terpendek 129 Km. Kata Kunci — Rute Terpendek, Graf, Algoritma Greedy, Algoritma Dijkstra Abstract — Finding distance a common problem for transport users from the start. This is because transportation users need a short distance and a short time in order to reach the trip quickly. Transportation problems often arise from remote locations, especially if there are transport users trying to go to a big city. Many algorithms have been used to help find the shortest route from one city to another, including the Greedy algorithm and Dijkstra's algorithm. In this study, the two algorithms were implemented to find the shortest path with a coverage area from Tuban Regency (as vertex T) to Surabaya City (as vertex S). The two algorithms used are compared using 4 (four) parameters, namely (1) algorithm time, (2) algorithm complexity, (3) algorithm programming sequence, and (4) distance traveled when completing the algorithm. From the comparison results, it can be concluded that the Greedy algorithm is superior in terms of execution time, complexity, and algorithm sequence, but for the shortest route, Dijkstra's algorithm is superior to the Greedy algorithm with the shortest route being 105 km, while the Greedy algorithm produces the shortest route 129 km. Keywords— Shortest Path, Graph, Greedy Algorithm, Dijkstra's Algorithm
Comparison Analysis of Graph Theory Algorithms for Shortest Path Problem Riti, Yosefina Finsensia; Iskandar, Jonathan Steven; Hendra, Hendra
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 12 No. 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1756

Abstract

The Sumba region, Indonesia, is known for its extraordinary natural beauty and unique cultural richness. There are 19 interesting tourist attractions spread throughout the area, but tourists often face difficulties in planning efficient visiting routes. From this case, it can be solved by applying graph theory in terms of searching for the shortest distance which is completed using the shortest path search algorithm. Then these 19 tourist objects are used to build a weighted graph, where the nodes represent the tourist objects and the edges of the graph describe the distance or travel time between these objects. Therefore, this research aims to compare the shortest path search algorithm with parameters to compare the shortest distance results, algorithm complexity and execution time for tourism in the Sumba area. The results of this research involve a comparison of several shortest path search algorithms, with the aim of finding the shortest distance results, algorithm complexity, and execution time for tourism in the Sumba area. Based on the test results of the five algorithms with the parameters that have been prepared, and the findings show that each algorithm has its own characteristics, the results are as follows: Dijkstra's algorithm can be used to calculate the shortest route for single-source and single-destination types. This resembles the Bellman-Ford algorithm, only the Bellman-Ford algorithm can be used simultaneously on graphs that have negative weight values. Meanwhile, the Floyd-Warshall algorithm is suitable for use on the all-pairs type. Then, the Johnson Algorithm can be used to determine the shortest path from all pairs of paths where the destination node is located in the graph. Finally, the Ant Colony algorithm to compute from a node to each pair of destination nodes.