Enhancing Data Precision Through Implementation of Chauvenet Criterion on ATmega328P Microcontroller for Data Filtering

The need for sensor measurements has increasing in recent years with sensor serve an essential function by capturing data and converting physical characteristics into electrical signals. In order to achieve high quality measurements, various methods and techniques are used to improve the performance of sensors and reduce the sources of error that can affect the measurement results one of them is by applying digital signal processing in filtering data. This research has investigated the effectiveness of the measurement using Chauvenet Criterion filtering on ATmega328P ADC reading using voltage sensor. The results showed that the regression polynomial has a high correlation with the voltage data (r2=0.99), indicating a successful calibration process. Additionally, the use of Chauvenet filtering resulted in more accurate and precise voltage readings of instrument 2 with an error of 0.0% compared to without filtering 0.03% and the measurement in instrument 1 0.2% on continuous data measurement in stable power supply. The readings using Chauvenet filtering on instrument 2 has a reading error of 0.21%, while instrument 1 has an error of 1.44% with 16.22 ± 1.95 ms per iteration from five samples data with standard deviation of 0.23 ± 0.01 under 3% noisy power supply conditions.