International Journal of Engineering, Science and Information Technology
Vol 5, No 2 (2025)

Implementation of Dijkstra and Ant Colony Algorithms for Web-based Shortest Route Search for LPG Gas Distribution

Rasna, Rasna (Unknown)
Irjii Matdoan, Moh. Rahmat (Unknown)
Kumala Dewi, Nurlaela (Unknown)
Ariffien, Afferdhy (Unknown)
Lamsir, Seno (Unknown)



Article Info

Publish Date
17 Feb 2025

Abstract

National energy needs and efforts to fulfill them are currently vital issues to be discussed and resolved. One type of energy that still has various problems is fuel gas, especially LPG (Liquid Petroleum Gas). The gas scarcity in each region differs; not all regions experience gas shortages, and some areas have excess LPG gas stocks. The problem of the scarcity of 3 kilogram (Kg) LPG gas is not the first time this has happened. In recent months, people in some regions have complained about the scarcity of subsidized 3-kilogram (kg) LPG gas. This situation certainly makes it difficult for the community. Not only does the scarcity hamper community activities, but it also makes the price of gas refills more expensive than usual. With the increasing demand for LPG gas every year, the government must provide large stocks of LPG gas. But what power if the LPG gas stock is less or runs out at specific locations. Therefore, applying gas base route search is needed to overcome the shortage of gas stock at a location. This application applies two search methods, namely the Dijkstra algorithm and the ant colony algorithm, to find the fastest route to the location of the gas base in the XYZ area. In the algorithm process, Dijkstra requires distance data for each city before starting the algorithm process. The Ant Colony Algorithm does not require the distance of each city because, in an Ant Colony, the distance between towns is calculated after the ants complete their journey. From the results of the process of the two algorithms, it is known that the path produced by Dijkstra's algorithm is more consistent and precise than the Ant Colony algorithm, which gives results that are not necessarily the same for each process.

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