To improve the quality and quantity of meteorological data over Indonesia, Meteorology Climatology and Geophysics Agency of Indonesia (BMKG) is continuously developing automatic weather observations. BMKG has 63 units Automatic Weather Station (AWS) and 165 units Automatic Weather Observation System (AWOS) both inside and outside the BMKG Station environment. To make the control of sensor conditions easier, especially for temperature, pressure, relative humidity, and rainfall sensors, an additional system is needed to monitor and warn when problems occur with these sensors. The correlation among weather parameters data is the key to monitoring the sensor condition, these data are going to be trained and tested with the Artificial neural network (ANN) method. Then, the sensor condition (normal or error indicated) can be well detected based on AWS’s data. The quality improvement of automatic weather station data is expected to increase the utilization of the data.
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