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All Journal Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Publikasi Teknik Informatika Nucleus Journal
Abdur Rohman Wakhid
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.
Hybrid AI–GA–DQN Optimization for Harmonic Mitigation in Smart Inverters arief budi laksono; Zainal Abidin; Abdur Rohman Wakhid; affan bachri; Wahri Sunanda; Wahyu Mulyo utomo
Nucleus Journal Vol. 5 No. 2 (2026)
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/nucleus.v5i2.5202

Abstract

This paper proposes a hybrid Artificial Intelligence–Genetic Algorithm–Deep Q-Network (AI–GA–DQN) control framework for inverter systems to minimize harmonic distortion and enhance dynamic voltage regulation. A mathematical state-space model incorporating harmonic dynamics is formulated, and a hybrid optimization approach is applied to adaptively tune modulation indices and switching parameters. The GA provides global parameter optimization, while DQN enables reinforcement learning-based adaptation under variable load conditions. MATLAB/Simulink simulations show that the proposed controller achieves a 75.6% reduction in Total Harmonic Distortion (THD), improves power factor to 0.995, and enhances system efficiency to 97.8%, compared with conventional PWM and GA-only controllers. The results confirm the effectiveness of the AI–GA–DQN strategy in achieving real-time harmonic suppression and superior transient performance in intelligent power converters.
Analisis Reliabilitas dan Akurasi Sensor Ultrasonik HC-SR04 terhadap Hasil Pengukuran Manual Akhmad Thariq Hafid; Ulul Ilmi; Abdur Rohman Wakhid
Jurnal Publikasi Teknik Informatika Vol. 5 No. 3 (2026): Jurnal Publikasi Teknik Informatika
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupti.v5i3.8061

Abstract

This study aims to analyze the reliability and accuracy of the HC-SR04 ultrasonic sensor compared to manual measurement results. The data used in this study are secondary data obtained from five previous studies in the form of distance measurement results using the HC-SR04 ultrasonic sensor and manual measurements as reference values. The data were analyzed using several statistical methods, including error analysis, mean, standard deviation, linear regression, correlation coefficient (R), Root Mean Square Error (RMSE), and sensor calibration. The results showed that the HC-SR04 ultrasonic sensor has good accuracy and reliability in distance measurement. The average relative error values obtained from each study were 0.81%, 1.54%, 1.52%, 2.28%, and 7.29%, while the RMSE values obtained were 0.6325 cm, 0.8367 cm, 0.1745 cm, 0.2429 cm, and 0.4323 cm. The correlation coefficient analysis showed a very strong relationship between the sensor readings and manual measurements, with R values ranging from 0.9827 to 1.0000. Furthermore, the linear regression analysis indicated that the changes in sensor readings followed the changes in manual measurement results linearly. The regression equations obtained were then used as the basis for the calibration process to reduce deviations between sensor measurement results and reference values. Based on the analysis results, the HC-SR04 ultrasonic sensor has good measurement performance, high consistency, and is suitable for use as an alternative digital distance measuring instrument.
Co-Authors Affan Bachri Akhmad Thariq Hafid Arief Budi Laksono Arif Budi Laksono Eko Wahyu Santoso Muhammad Chusni Marzuki Ulul Ilmi Wahri Sunanda Wahyu Mulyo utomo Zainal Abidin