<![CDATA[This study aims to develop a web-based waste financial management system in Guwosari Village integrated with a payment delay prediction feature. The system is designed to improve the efficiency of waste payment management that was previously handled manually. The system development employs the Waterfall method, consisting of requirements analysis, system design, implementation, and testing. The payment delay prediction model is built using the Decision Tree algorithm, utilizing customer data and transaction payment history from the last six months. The developed system supports multiple user roles, including superadmin, admin, agent, and customer, and provides features such as digital transaction recording, notifications, and automated financial reports. The evaluation results indicate that the system enhances efficiency in waste financial management and reduces the risk of recording errors. The prediction model achieves an accuracy rate of 85.06% in identifying customers who are likely to experience payment delays. In conclusion, the proposed system serves as an effective digital solution for waste financial management, although it is still limited by the use of a single algorithm and data coverage restricted to one area.]]>
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