This research seeks to assess the effectiveness of backtracking algorithms in ensuring success rates during usability testing of digital product prototypes. The UX/UI review process must produce fast and objective results with minimal resources in a digital era that requires high speed and accuracy. This research implements a heat map tracking method with several valid variables, namely font size, button size and location, and navigation flow, which are then analyzed using a backtracking algorithm to assess design performance based on the user's level of success in completing the task. The research results show that the backtracking algorithm is able to speed up evaluation time by up to 45% and reduce dependence on manual observation, without reducing the accuracy of the results. Designs with a success rate above 80% are categorized as good, while designs below 60% are considered to need improvement. This method is not only time and resource efficient but can also be used in Agile-based iterative digital design processes. The study suggests combining these strategies with additional techniques, including eye tracking or machine learning, to improve progress.
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