Dijkstra's Algorithm for Optimizing Humanitarian Aid Distribution Routes to Flood Victims in Cerme District, Gresik
DOI:
https://doi.org/10.33005/jasid.v2i01.32Keywords:
djikstra's algorithm, shortest route, flood, gresikAbstract
This study presents the development and analysis of a system designed to optimize the distribution routes of social aid during flood emergencies in the Cerme District, Gresik Regency. The primary objective is to ensure that logistical operations, particularly the delivery of aid to affected villages, are carried out in the most efficient and timely manner. To achieve this, Dijkstra’s Algorithm is employed due to its well-established reliability in computing the shortest path between nodes in a weighted graph. The graph used in this research is constructed based on real-world spatial data, with each node representing a village and the edges representing actual road distances obtained from mapping services. The system is implemented using an Object-Oriented Programming (OOP) paradigm in Python, which ensures modularity and scalability of the codebase. For graph modeling and shortest path computation, the NetworkX library is utilized, while the graphical user interface (GUI) is built using Tkinter to provide an interactive and user-friendly experience. The application enables users to select starting and destination points from dropdown menus, compute the shortest route dynamically, and visualize it on an interactive graph complete with route details and distances. Experimental trials were conducted by simulating various flood scenarios, and the results demonstrated that the system successfully identified optimal aid routes with minimized travel distances. These outcomes confirm the practicality and effectiveness of the proposed method. Moreover, the ability to update the graph dynamically allows the system to adapt to changes in road accessibility due to flooding. This makes the tool highly applicable in real-world disaster response scenarios. In conclusion, the developed application offers a valuable solution for both local government agencies and humanitarian volunteers, helping to improve coordination, reduce delivery time, and ensure that aid reaches flood-affected communities as efficiently as possible.
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