<![CDATA[This research implements Ant Colony Optimization (ACO) to optimize waste collection routes in urban areas. The implementation utilizes the PHP, JS, and HTML programming languages, resulting in an interactive mapping application that facilitates community participation in identifying garbage accumulation locations. The research findings indicate that by employing ACO calculations with parameters α = 1.0 for pheromones and β = 2.0 for visibility, the best waste collection route was identified with a total distance of 9.565 km.The route begins at "Cunda Fish Market" (pheromone 0.1, visibility 3.321146121) heading towards "Beside the bus terminal" (distance 0.301 km), then continues to "Inpres Market" (pheromone 0.1, visibility 0.814261078, distance 1.228 km), "Pusong Lama Market" (pheromone 0.1, visibility 0.611779235, distance 1.635 km), "Lhokseumawe Reservoir behind the church" (pheromone 0.1, visibility 1.854365059, distance 0.539 km), and concludes at "Lhokseumawe State Polytechnic" (pheromone 0.1, visibility 0.170600122, distance 5.862 km).Each step reflects ant choices based on calculated probabilities, starting from the highest probability of 0.922322 in the first step to the lowest probability of 0.006391 in the last step. This research underscores the efficiency of the routes generated by ACO and demonstrates that bio-inspired algorithms such as ACO can be effectively applied to real logistics problems, providing responsive and adaptive solutions to the dynamics of urban environments.]]>
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