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In recent years, the gait stability was analyzed through several methods on various type of signal that related to the recurrence properties of this movement. The gait stability analysis methods came up with several quantifiers to express its stability. Based on several recent research, the most used methods to quantify a gait movement were Lyapunov Exponent (LE) and Recurrence Quantification Analysis (RQA). The comparison of these methods with the variation of walking speeds were evaluated in this research to obtain the most reliable quantifiers for the gait stability analysis. The gait of eleven participants of 22 ± 0.85 years old with a BMI of 21.76 ± 2.06 kg/m2 were tracked by a 3D optical motion capture system by using four action cameras as the data acquisition equipment. To test the effect of walking speed variation, each subject then performed the walk on the treadmill with a speed of 70%, 100%, and 130% of their natural walking speed. The gait data used in this study for the LE and RQA methods were the joint angular positions and joint angular accelerations, respectively. Both methods used 5 of embedding dimensions and 10% of a cycle as the time delay. The quantifiers that are evaluated were short Lyapunov Exponent (sLE) and long Lyapunov Exponent (lLE) for the LE method, and Recurrence Rate (RR) and Determinism (DET) for the RQA method. This research show that the most reliable quantifiers to analyze the gait stability were short Lyapunov Exponent (sLE) and Determinisim (DET) on the knee joint as the object of analysis. By the increased of walking speed, the sLE shows that the subjects tend to have a lower fall risk and the DET shows that the subject walk more stable.