<![CDATA[Purpose: Electricity is a crucial necessity, serving as a prerequisite for the smooth, efficient, safe, and comfortable conduct of human life activities. The energy requirements for each household, especially in shared living spaces like dormitories, vary, with residents' behaviors and habits influencing daily electricity usage patterns. Wasteful electricity habits can lead to disadvantages for various parties. To address this, control technology has been developed to reduce the risk of injustice in billing and electricity usage among dorm residents, aiming to optimize electrical load usage. Research Methodology: This research utilizes the backpropagation method to develop a complex calculation model for predicting monthly electricity token expenditures based on daily electricity usage. The methodology involves understanding and analyzing the electricity consumption patterns of dorm residents, implementing the backpropagation algorithm, and testing the model's accuracy in predicting future electricity expenses. Results: The study presents insights gained from applying the backpropagation method, demonstrating its effectiveness in predicting monthly electricity token expenditures. Results include the development of a model that takes into account daily electricity usage patterns, allowing residents to better control and plan their electricity expenses. Limitation: It is important to note that this research is confined to the development of a predictive model using the backpropagation method. Practical implementation and testing of the model in real-world dormitory settings are beyond the scope of this study. Future research and application stages are warranted to validate the model's effectiveness and usability. Contribution: This research contributes by providing a predictive model using the backpropagation method, offering dormitory residents a tool to estimate and control their monthly electricity expenses. The model aims to reduce wasteful electricity practices and promote fair billing, contributing to a more sustainable and equitable electricity usage environment.]]>
