Developing a Rule-Based System to Recommend Household Budget

Household budgeting is crucial for financial stability, yet many individuals find it challenging due to the lack of structured financial planning tools. This paper introduces a rule-based system that optimizes expenses by considering family size, income, and spending behavior. Unlike traditional budgeting tools, our system dynamically distributes income across essential categories such as housing, food, medical care, education, and savings using predefined rules. The system leverages dynamic input processing and predefined allocation rules to provide real-time insights into budgeting constraints. Experimental results show that the proposed model achieves 90% accuracy in budget allocation, ensuring financial sustainability and preventing overspending. Our system provides a transparent, flexible, and user-friendly alternative to machine learning-based budget models, making it accessible to households of all financial backgrounds.