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Two-thirds of Indonesia's territory is waters that have a high risk of flooding. Bathymetric surveys are important for flood management because they provide depth and topography data to determine the need for dredging of a water area. Traditional bathymetric surveys produce less than optimal coverage due to limited ship movements. This research aims to develop an automatic bathymetry system using a ping sonar echosounder sensor integrated with a USV (Unmanned Surface Vehicle). The ping sonar echosounder produced by ROVMAKER can generally only be accessed using the built-in software from the ROVMAKER manufacturer and can now be integrated with the microcontroller system on the USV to increase the efficiency of bathymetric system performance. This research also uses the Kalman filter method to reduce sensor reading noise. Validation of the suitability of the sensor shows an average error of 2.94% at a depth of 1400mm and 2.195% at a depth of 2200mm, which shows that the sensor is classified as suitable for use. The optimal noise reduction in the Kalman filter experiment is at a variance ratio (R/Q) of 1000 with an RMSE of 5.05mm at a depth of 1400mm and 3.99mm at a depth of 2200mm. This system has been proven to increase the accuracy of bathymetric data and system access efficiency.





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