Rifdah Syahputri; Alwi Andika Panggabean; Lailan Sofinah Harahap
Victory in Mobile Legends is influenced by various factors, such as player skills, strategy, and character selection. To predict game outcomes, the backpropagation algorithm is applied to process historical gameplay data and create an accurate predictive model. This study aims to apply the backpropagation algorithm to predict victory based on player attributes, including team role, experience level, and past performance. The research method involves training and testing the model using data from multiple gameplay sessions with varied outcomes. Findings show that the backpropagation algorithm can predict game results with high accuracy, especially when the data includes a more comprehensive range of attributes. The implications of this study suggest that a backpropagation-based predictive model can help players understand their chances of winning and optimize their gameplay strategies. Furthermore, future developments in this algorithm could provide benefits for similar applications in other digital gaming fields.