<![CDATA[A power supply is a primary electrical source for electronic systems, and its voltage accuracy is essential for maintaining stable system performance. This study aims to calibrate and evaluate the voltage accuracy of a power supply using the INA219 sensor via a simple linear regression implemented in Google Colab. The novelty of this study lies in integrating the INA219 sensor, simple linear regression, and the open-source Google Colab platform into a practical, low-cost, and easily reproducible calibration workflow. The results show a very strong linear relationship between the power supply voltage and both the INA219 sensor and the digital multimeter, with a coefficient of determination (R²) of 1.00 in both cases. Measurements using the INA219 yielded an average error of 0.04 V, an RMSE of 0.00409 V, and an accuracy of 99.93%, while the digital multimeter yielded an RMSE of 0.002954 V with the same accuracy. These findings indicate that both instruments exhibit excellent linearity and precision, although the digital multimeter shows slightly higher measurement consistency. Overall, the INA219 sensor is proven to be a reliable low-cost alternative for voltage measurement with high accuracy and has strong potential for application in electronic testing and renewable energy systems. ]]>
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