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All Journal Journal of Electrical Engineering and Computer (JEECOM) Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal JEETech Nucleus Journal
Eko Wahyu Santoso
Universitas Islam Lamongan
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

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Rancang Bangun Sistem Monitoring Digester Biogas Berbasis IoT dengan Sensor Multi-Parameter Zainal Abidin; Nur Azizah Affandy; Eko Wahyu Santoso
Jurnal JEETech Vol. 6 No. 2 (2025): Nomor 2 November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v6i2.6210

Abstract

This research aims to design and implement a monitoring system for key parameters in the biogas production process, namely temperature, humidity, and pH of cow dung liquid using Internet of Things (IoT) technology. This system is designed to support the efficiency and reliability of the anaerobic fermentation process in a biogas plant digester developed in a livestock environment. A DHT11 sensor is used to measure temperature and humidity, while an analog pH sensor is used to measure the acidity level of the liquid in the digester. All data is transmitted in real time via an ESP8266 module to the ThingSpeak cloud platform, which allows for online data visualization and analysis. Test results show that the system is able to operate stably with an accuracy of ±1°C for temperature, ±3% for humidity, and ±0.2 for pH compared to conventional measuring instruments. This system is expected to assist farmers in continuously monitoring biogas conditions and become the basis for automation of fermentation process control in the future.
Sistem Cerdas Budidaya Jamur Tiram Berbasis Internet Of Things (IoT) Eko Wahyu Santoso; Affan Bachri; Aura Arif Darmawan
Jurnal JEETech Vol. 6 No. 2 (2025): Nomor 2 November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v6i2.6206

Abstract

The cultivation of oyster mushrooms (Pleurotus ostreatus) requires optimal temperature and humidity control to ensure maximum growth. One of the main challenges faced by mushroom farmers is the difficulty in monitoring and controlling environmental conditions in real time, which can negatively impact yield quality and productivity. This study aims to design and implement an intelligent system based on the Internet of Things (IoT) to automatically monitor and regulate temperature and humidity in oyster mushroom cultivation rooms. The system utilizes an ESP32 microcontroller as the main controller, a DHT11 sensor for temperature and humidity measurement, a relay module as an automatic switch, a mist maker to maintain humidity, and a DC fan to control air circulation. Environmental data are transmitted in real time to a Telegram Bot application, allowing users to monitor conditions remotely via smartphones. The experimental results show that all system components functioned properly and responsively. The DHT11 sensor accurately detected temperature and humidity variations, the relay operated stably in controlling connected devices, the mist maker effectively increased humidity, and the DC fan successfully reduced room temperature. In addition, the Telegram Bot provided automatic notifications and responded to user commands without noticeable delay. Overall, the IoT-based intelligent system proved effective in maintaining stable environmental conditions for oyster mushroom cultivation, improving monitoring efficiency, and supporting farmers in enhancing both yield quality and productivity.
Optimalisasi Auto Dosing Cement Additive Berbasis PLC-SCADA dengan Kendali Closed-Loop pada Finish Mill Affan Bachri; Moch Syafi Uddin; Eko Wahyu Santoso; Abd Kadir Mahamad
Nucleus Journal Vol. 5 No. 1 (2026): May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/nucleus.v5i1.5110

Abstract

PLC is a programmable logic control system that uses a microprocessor as the main controller and is widely applied in industrial automation processes such as monitoring and controlling production machinery. The system is equipped with input and output devices that interact with external components such as buttons, sensors, actuators, and other hardware devices. This technology has been implemented in various fields, including cement production processes. In this study, the programmable logic controller was used to modify the auto dosing system for cement additive with the aim of improving dosing accuracy, enabling real-time monitoring, and developing an auto dosing system capable of adapting to changes in feed material. The previous system operated manually and relied heavily on operator intervention, resulting in inconsistent dosing performance. To overcome these limitations, a programmable logic controller-based control system integrated with a supervisory control and data acquisition system was implemented. The system applied a closed-loop control method to regulate the dosing process in order to achieve stable and consistent output. System performance was evaluated by comparing the accuracy and stability of the flow rate before and after modification. The analysis results showed that the proposed system reduced the error between the setpoint and the actual flowmeter reading from 16% to 3%, decreased flow fluctuations, and improved process stability. In addition, the system enabled centralized monitoring and reduced operator dependency, thereby improving operational efficiency.
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.
Real-Time Monitoring of Solar Battery and Lamp Conditions Using Internet of Things Affan Bachri; Arief Budi Laksono; Eko Wahyu Santoso; Achmad Rifqi Adi Firmansyah
Journal of Electrical Engineering and Computer (JEECOM) Vol 8, No 1 (2026)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v8i1.16851

Abstract

Solar photovoltaic battery systems require continuous observation to prevent unnoticed voltage decline, abnormal temperature, and lamp failure. This study developed a compact Internet of Things monitoring prototype using an ESP32 microcontroller, an INA219 sensor for voltage, current, and power, an LM35 sensor for battery temperature, and a light-dependent resistor for lamp-state detection. Sensor data were shown locally on a 16x2 liquid-crystal display and transmitted through Wi-Fi to a Blynk dashboard at a five-second update interval. The study applied experimental and engineering research procedures covering hardware design, software integration, component validation, and integrated tests under off, three load, and charging conditions. The INA219 achieved average accuracies of 99.69% for voltage, 99.32% for current, and 99.49% for power, while the LM35 reached 97.08% accuracy. The light sensor correctly separated the tested off condition at 3 lux from lamp-on conditions between 230 and 2100 lux. Across all operating modes, the local display and Blynk presented consistent measurements, and negative current reliably indicated charging. The prototype therefore provides accessible real-time monitoring of battery electrical behavior, temperature, charging direction, and lamp status, although long-term data logging and field-scale validation remain necessary.
Co-Authors Abd Kadir Mahamad Abdur Rohman Wakhid Achmad Rifqi Adi Firmansyah Affan Bachri Arief Budi Laksono Arif Budi Laksono Aura Arif Darmawan Moch Syafi Uddin Muhammad Chusni Marzuki Ulul Ilmi Zainal Abidin