<![CDATA[Private schools need help in handling school fees and financial processes. Traditional manual payment systems result in data processing issues, delayed financial reporting, and complications from misplaced records. Late fee payments threaten school income, which is crucial for staff salaries. Modern solutions are imperative. Desktop applications have limitations, requiring installation on specific devices, leading to compatibility concerns. This research opts for a web-based application. It employs prototyping models and predictive abilities using the Naïve Bayes algorithm. The web-based application aims to streamline fee management and predict payment delays, enhancing financial transaction management while prioritizing data security through database encryption. This web-based solution aligns with private schools' operational needs, simplifying payments and increasing late payment prediction accuracy. Extensive black-box testing validated its suitability, satisfying administrative staff needs. Four test cases gained administrative team approval. This innovation empowers private schools to optimize operations and financial management. In summary, the research tackles critical financial challenges private schools face by introducing a web-based application that simplifies payment processes, enhances accuracy in predicting late payments, and aligns seamlessly with administrative needs.]]>
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