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Abstract

This study aims to evaluate the performance of various types of Light Dependent Resistor (LDR) sensors as alternative luxmeters based on Arduino using exponential and power regression calibration methods. Four LDR types—GL5506, GL5528, GL5537, and GL5539—were tested under controlled lighting conditions using a dimmable smart bulb with light intensity variations from 5% to 100%. A commercial GM1030C luxmeter was used as the calibration reference. The measured data were analyzed using statistical parameters, including the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and mean percentage error, to determine the accuracy and stability of each sensor. The results show that all sensor types achieved R² values ranging from 0.9772 to 0.9992, indicating that both regression models effectively represent the nonlinear relationship between sensor output and actual light intensity. The GL5506 sensor exhibited the best accuracy with R² = 0.9962, RMSE = 13.13 lux, MAE = 11.1 lux, and an average error of 2.89% using the power regression model. The power regression model performed better for sensors with fast and linear responses (GL5506 and GL5528), while the exponential regression model was more suitable for sensors with gradual nonlinear responses (GL5537 and GL5539). With overall errors below 7%, all LDR sensors tested are suitable for use as economical and reliable Arduino-based luxmeters for educational and basic research applications.

Keywords

LDR Luxmeter Calibration Exponential Regression Model Power Regression Model LDR Luxmeter Kalibrasi Regresi eksponensial Regresi power

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Copyright (c) 2025 Heriansyah Heriansyah, Fades Br Gultom

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How to Cite
Heriansyah, H., & Gultom, F. B. (2025). EVALUATION OF THE PERFORMANCE OF VARIOUS TYPES OF LDR SENSORS AS LUXMETERS THROUGH EXPONENTIAL AND POWER REGRESSION CALIBRATION. Jurnal Kumparan Fisika, 8(3), 87–94. https://doi.org/10.33369/jkf.8.3.87-94
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