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All Journal Malcom: Indonesian Journal of Machine Learning and Computer Science
Muhammad Chusni Marzuki
Universitas Islam Lamongan
Computer Science & IT

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Performance Evaluation of the DHT11 Sensor for MATLAB-Based Temperature and Humidity Measurements Muhammad Chusni Marzuki; Ulul Ilmi; Arif Budi Laksono; Eko Wahyu Santoso; Abdur Rohman Wakhid
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 2 (2026): MALCOM April 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i2.2565

Abstract

This study evaluates the performance of the DHT11 sensor in measuring temperature and humidity by comparing it with a conventional thermometer using a MATLAB-based statistical approach. The analysis includes descriptive statistics, error evaluation using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE), linear regression modeling, and significance testing through ANOVA and the Durbin–Watson test. The results show that the DHT11 sensor provides consistent measurements (good precision) and exhibits a strong linear relationship with the reference instrument, as indicated by a high correlation coefficient (R = 0.944) and coefficient of determination (R² = 0.891). However, the sensor demonstrates a slight systematic bias, with temperature readings approximately 1–2 °C higher than those of the conventional thermometer. The obtained error values (MAE = 1 °C and MAPE ? 3.4%) indicate acceptable accuracy for general monitoring applications. Overall, the DHT11 sensor is a reliable, cost-effective, and practical solution for temperature and humidity monitoring. Nevertheless, calibration is recommended to improve measurement accuracy in applications requiring higher precision.
Co-Authors Abdur Rohman Wakhid Arif Budi Laksono Eko Wahyu Santoso Ulul Ilmi