Cloud-based game streaming has the potential to deliver high-quality gaming experiences anywhere by streaming game frames as video from servers to clients. However, frame jitter from bandwidth and delay variability can substantially degrade the user experience. While traditional streaming systems use playout buffer to smooth over frame variability, playout buffer algorithm in cloud-based game streaming remains underexplored. This thesis investigates the effectiveness of playout buffer algorithms for cloud gaming through the implementation of a custom game streaming platform and an automated Flappy Bird-style game. We evaluated two buffer strategies, the E-Policy and the Queue Monitoring (QM) under controlled jitter conditions. By applying existing Quality of Experience (QoE) models, we measure how the critical metrics of delay and interrupts influence users' perceived gaming quality. Our results suggest that the EPolicy reduces playback interruptions but causes higher delay, which lowers overall QoE, especially when network jitter is high. On the other hand, the QM algorithm with higher decay values keeps a better balance between delay and playback smoothness, leading to higher combined QoE across different network conditions.