Optimization of Searching for the Closest Route to Futsal Fields in Jayapura City Using the Greedy Algorithm

The increasing popularity of futsal in Jayapura City has created a growing demand for efficient access to information regarding available sports facilities. However, the lack of an integrated digital platform leads to inefficiencies in locating and booking futsal fields, often forcing users to rely on manual communication or generic navigation services that lack real-time data. This study aims to develop an Android-based application that optimizes the search for the nearest futsal field using the Greedy Algorithm (GA). The system integrates the Google Maps API, the Firebase Realtime Database, and Kotlin/Java to provide real-time field availability, route visualization, and online booking features. The research employed the Waterfall development model, with data collected through observation, interviews, and a literature review, involving 19 futsal fields in Jayapura City. System testing was conducted using Black-Box Testing and User Acceptance Testing (UAT). The results show that implementing the Greedy Algorithm increased route efficiency by 22%, reduced search time by 55%, and achieved 93.2% user satisfaction. All core functions passed functionality testing without errors. This study contributes both practically and theoretically by demonstrating the potential of heuristic-based optimization in sports facility management and promoting smart-city digitalization in urban sports infrastructure.