The Kalman Filter is very useful in prediction and estimation. In this paper, the Kalman Filter is implemented for Inertial Measurement Unit (IMU) on the ATMega8535. The sensors used in this system are accelerometer MMA7260QT and gyroscope GS-12. The system chooses the arbitrary sampling time and then it is evaluated for possible using smaller value. As the Kalman Filter operation needs matrix calculation, the formula is converted into several ordinary equations. The parameter being investigated in this paper is measurement covariance matrix. This parameter influences the way the Kalman Filter responses to noise. Bigger value makes the Kalman Filter less sensitive to noise and the estimation is too smooth, thus it does not give real angle estimation. Using smaller value makes the Kalman Filter more sensitive to noise. This makes the estimated angle still suffers from noise and it is likely that the Kalman Filter is useless. This paper recommends 0.0001 to 0.001 for the measurement covariance noise parameter. This paper also recommended a pipeline configuration if the control algorithm needs more space in a sampling time.