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

doi:10.57152/malcom.v6i2.2565

Authors

Muhammad Chusni Marzuki Universitas Islam Lamongan
Ulul Ilmi Universitas Islam Lamongan
Arif Budi Laksono Universitas Islam Lamongan
Eko Wahyu Santoso Universitas Islam Lamongan
Abdur Rohman Wakhid Universitas Islam Lamongan

DOI:

https://doi.org/10.57152/malcom.v6i2.2565

Keywords:

DHT11 Sensor, Humidity Measurement, Linear Regression, Statistical Analysis, Temperature Measurement

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.

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References

I. A. Widhiantari, I. K. W. Widiastawan, and N. K. I. Prasistha, “Monitoring of internal and external air temperature and humidity in oyster mushroom cultivation house using the DHT11 sensor,” J. Online Pertanian Tropika, vol. 12, no. 1, pp. 16–23, 2025.

Y. F. Mahfud, “Temperature and humidity monitoring system for oyster mushroom seeding room,” Faculty of Engineering, Universitas Sultan Ageng Tirtayasa, 2023.

H. Rofiqi, “Strength analysis of IoT-based automatic sprayer for mushroom cultivation,” Politeknik Negeri Jember, 2024.

J. C. N. Putra and R. P. Astutik, “PLC-based temperature and humidity controller design for oyster mushroom cultivation using Node-RED platform,” G-Tech J. Teknologi Terapan, vol. 9, no. 1, pp. 130–139, 2025.

L. A. Kusumo, “Application of median filter in temperature and humidity data processing using DHT11 and DHT22 sensors,” Krisnadana Jurnal, vol. 4, no. 2, pp. 103–110, 2025.

A. Raj, S. Gupta, G. Singh, A. Parashar, and K. Kumar, “Development of an IoT-enabled intelligent monitoring framework,” in Proc. 4th Int. Conf. on Advanced Computing and Innovative Engineering Technologies (ICACITE), 2024, pp. 639–643.

I. Nandang and R. K. Dewi, “Effectiveness of DHT11 sensor as an indicator of temperature and humidity in baby incubator,” Java Health Journal, vol. 8, no. 3, 2021.

M. R. Fauzi and H. Mukhtar, “Design of room temperature control system using Arduino-based DHT11 sensor,” Proc. 1st Celscitech-UMRI, vol. 1, pp. 122–126, 2016.

S. M. Masrukin, A. I. Agung, N. Kholis, and M. S. Zuhrie, “Design of a smart egg incubator for maintaining stable temperature and hatch efficiency using Arduino Uno and DHT11 module,” J. Electrical Engineering, vol. 11, no. 1, pp. 1–7, 2022.

A. B. Aruan, “Development of a temperature and humidity controller device for room environment using Arduino-based DHT11 sensor,” Universitas Sumatera Utara, 2019.

I. Aditia, R. Ilham, and J. P. Sembiring, “Automatic egg hatching device using DHT11 sensor with Arduino,” J. Ilmiah Mahasiswa Kendali dan List, vol. 3, no. 1, pp. 113–119, 2022.

F. Gumilang, L. Lenni, and A. Kurniawan, “Prototype monitoring and temperature control of incubator via Telegram using Arduino-based DHT11,” J. Teknik Elektro, vol. 7, no. 1, pp. 1–7, 2023.

B. J. Punzalan, “Performance evaluation of object detection system integrating DHT11 sensor and servo motor,” SSRN Repository, ID 5255264, 2025.

M. Rajunaik, S. Ajmera, M. D. Sri, K. S. Praneeth, and P. M. Sai, “Autonomous robot for live video surveillance using DHT11 and gas sensors,” Integrated Technologies in Electrical, Electronic and Biotechnological Engineering, CRC Press, pp. 252–255, 2025.

K. S. Praneeth and P. M. Saif, “Prototype of autonomous video surveillance robot using DHT11 and MQ2 sensors,” Integr. Technol. Electr. Electron. Biotechnol. Eng., p. 252, 2025.

R. J. Syahputra, M. Sihombing, and D. Saripurna, “IoT-based monitoring of room temperature and humidity using DHT11 sensor,” J. Artificial Intelligence Engineering and Applications, vol. 3, no. 1, p. 364, 2023.

S. Suharjianto, “Design and automation of lighting, temperature, and humidity control for oyster mushroom cultivation using microcontroller in Lamongan region,” JE-Unisla, vol. 2, no. 2, pp. 87–92, 2017.

I. K. Wardani et al., “Study on precision and accuracy evaluation of DHT22 module in monitoring greenhouse temperature and humidity,” IOP Conf. Ser.: Earth and Environmental Science, p. 12146, 2023.

M. F. Aulia and A. Wagyana, “Accuracy evaluation of humidity and temperature sensors for vertical garden monitoring,” Proc. Seminar Nasional Inovasi Vokasi, pp. 1186–1194, 2025.

J. Pebralia, Y. Fendriani, M. F. Afrianto, and C. N. Syaqila, “Design of light intensity, temperature, and humidity measurement system using DHT11 and BH1750 sensors,” J. Online Physics, vol. 10, no. 1, pp. 37–42, 2024.

S. Gomathi and M. R. Devi, “IoT-based automated onion storage solution utilizing DHT11 and MQ-6 modules,” in Proc. 5th Int. Conf. on Smart Electronics and Communication Systems (ICOSEC), 2024, pp. 1–5.

S. R. Auliany, A. Dani, and A. D. Tarigan, “Implementation of DHT11 and YL-69 sensors in IoT-based automatic plant watering system via Blynk app,” J. Pendidikan Sains Sosial dan Agama, vol. 10, no. 2, pp. 168–183, 2024.

A. Sudaryanto, A. Kridoyono, et al., “Evaluation of DHT11 sensor accuracy for monitoring temperature and humidity in egg incubation,” J. Informatics, Electrical & Electronic Eng., vol. 4, issue 1, pp. 1–6, 2024.

M. Tamilarasan, “IoT-based smart agriculture monitoring and control system,” 2024.

X. Zhang, S. Zhang, and J. Yan, “PCP-MAE: a predictive model for estimating the center of masked autoencoders,” Advances in Neural Information Processing Systems, vol. 37, pp. 80303–80327, 2024.

M. Boch, C. Hirsch, Y. Susaki, S. Gindl, and M. Tauber, “Innovation analysis via decentralized MAPE-K feedback in cyber-physical production environments,” in Proc. IEEE NOMS, 2024, pp. 1–7.

J. Shavkiev et al., “Multifactorial ANOVA study of genotype and environmental effects on cotton morphological and agronomic traits,” J. Wildlife Biodiversity, vol. 9, no. 2, pp. 388–408, 2025.

L. Tan, S. Wei, X. Xu, and J. Morphew, “A comparative study of regression and covariate approaches extending beyond ANOVA in engineering education,” European Journal of Engineering Education, vol. 50, issue 4, pp. 878–908, 2025.

R. A. Purba, “IoT-based smart farming system for hydroponic plants,” Institut Teknologi Sepuluh Nopember, 2025.

M. R. Hersydano, S. G. Pamungkas, I. G. L. D. Putra, A. Rahman, and A. M. Warohma, “IoT-based greenhouse monitoring system design,” in Proc. MDP Student Conf., pp. 483–490, 2025.

A. N. Habby and H. Septanto, “IoT-based prototype for air temperature and water level monitoring in hydroponic house,” J. Pengembangan Pendidikan, vol. 9, no. 3, 2025.

W. Arif, “Development of indoor hydroponic agriculture monitoring system using Internet of Things (IoT),” Universitas Andalas, 2025.