Jurnal Otomasi Kontrol dan Instrumentasi

Prototype of 100 ml Measuring Cylinder Pouring Tool using Microcontroller-Based Servo Motor

2025-04-23T12:01:04+07:00

Pouring liquid from a measuring cylinder requires careful consideration of the appropriate tilt angle to achieve optimal emptying conditions. Drip time and emptying time are critical parameters for maximizing pouring efficiency. This study presents the design of a microcontroller-based system to automate the pouring process of a measuring cylinder. The developed prototype utilizes an MG996R servo motor as the actuator and an Arduino Uno microcontroller as the control unit. The system comprises two main components: a servo motor-based mechanical pouring structure and microcontroller-based automation software. The initial phase involved designing the structure using 3D modelling software, manufacturing, and manual assembly. Simulations were conducted using SolidWorks software. Experimental results showed that the liquid pouring time at a 120° angle was 9.89 seconds with a 4.76% error, at 150° was 12.38 seconds with a 3.78% error, and at 170° was 13.97 seconds with a 2.73% error. The total emptying time for a 100 ml measuring cylinder was recorded at 62.69 seconds with a 0.81% error.

Zentra: Meja Belajar Pintar Portabel Berbasis Iot Untuk Gen Z

2025-05-21T15:26:07+07:00

The advancement of technology has significantly influenced future generations, including Generation Z. This generation is highly dependent on technology, especially in learning activities. However, learning effectiveness is often disrupted by environmental factors such as room temperature, poor lighting, and back pain due to prolonged static sitting posture. This research aims to design a portable smart study desk based on the Internet of Things to improve learning comfort and productivity. The system is developed using an ESP32 microcontroller connected to several sensors. The FSR402 sensor detects arm pressure as an indicator of sitting posture, the DHT22 monitors temperature and humidity, and the LDR senses ambient lighting. Additionally, the desk is equipped with a cooling fan controllable via smartphone. Sensor data is transmitted in real-time to the Blynk platform and supported by a notification system to alert the user. Accuracy testing was conducted using reference tools such as a thermohygrometer and a luxmeter, along with evaluating the effectiveness of the laptop cooling feature. The results show that the system can provide accurate environmental data and support more productive and effective study sessions. These findings highlight the potential for further development of adaptive IoT-based learning tools tailored to modern user needs.

Development of Surface Plasmon Resonance (SPR) Device as Biosensor Transducer

2025-09-02T13:06:51+07:00

This study developed a simple and cost-effective laboratory-scale Surface Plasmon Resonance (SPR) device called β SPR. SPR is a sensitive, real-time, and non-labeling technique widely used to detect the concentration and quality of solutions. However, the very high price of commercial SPR devices is a barrier, so a portable and affordable version was developed. The β SPR device uses a Kretschmann configuration with a 670 nm laser, a polarizer, and a modified Porro BA4010 prism for a simpler and more efficient optical configuration. A thin gold film (~50 nm) is placed on the prism using immersion oil, and the test solution is flowed through a flow cell. The laser is fired at a 90° angle to induce p-polarized waves that trigger surface plasmon resonance. This phenomenon decreases the light reflectance, forming a dip curve used for analysis. The device was tested using glucose solution (0.05–0.27 M) and compared with a commercial SPR device (α SPR). The results show a shift in the angle with increasing concentration. The highest error was 6.53% at 0.05 M, and the lowest was 0.94% at 0.27 M. The β SPR sensitivity was recorded at 4.41⁰/M, showing promising performance for cost-effective biosensor applications.

Design and Development of a Low-Cost Arduino-Based Pultrusion System with Integrated Heating and Cutting Control for Converting Polyethylene Terephthalate Bottle Waste into 3D Printing Filament

2025-09-03T18:26:47+07:00

Plastic waste, particularly polyethylene terephthalate (PET) bottles, has emerged as a critical global challenge. Single-use plastic production has continued to increase, while Indonesia generates millions of tons of waste annually, with a significant portion being plastic. To address this issue, this study presents the design of a low-cost Arduino-based pultrusion system for recycling PET bottles into 3D printing filament. Unlike existing open-source solutions that rely on manual or separate processing stages, the proposed system integrates heating, cutting, and cleaning modules into a single automated workflow with real-time control of motor speed and nozzle temperature. Experimental results show that filament tensile strength depends on pultrusion temperature, reaching 67.66 MPa at 195 °C, 62.08 MPa at 185 °C, and 58.64 MPa at 175 °C. Energy analysis indicates that the heater consumed of 0.203 kWh to reach the set-point and 0.509 kWh after one hour, while the pultrusion drive consumed 0.00233 kWh and 0.0257 kWh, respectively. Compared with values reported in prior studies, the tensile strength obtained is within or above typical PET filament ranges. These findings demonstrate that the developed system reduces manual handling, improves efficiency, and produces reliable, energy-efficient filament suitable for additive manufacturing.

Design of a Temperature and Humidity Monitoring System Based on the Internet of Things for Cold Chain Vaccine Storage

2025-08-07T14:35:01+07:00

Temperature and humidity monitoring are important aspects of the cold chain vaccine storage system for preserving quality. Manual temperature recording risks missing readings, which compromise the vaccine quality. Excessive humidity may cause condensation on packaging, while very low humidity can reduce the stability of certain vaccines. This research aimed to design and build an Internet of Things (IoT) monitoring system with real-time notifications and website integration to support the vaccine storage cold chain system. The system used an ESP32 microcontroller, an SHT31 sensor, and dual storage (Firebase and SD Card). Development utilized Arduino IDE, Next.js framework, Telegram bot, Firebase, and Visual Studio Code editor. Tests included accuracy measurement, received signal strength indicator (RSSI) measurement, notification and data monitoring for several days. Performance was tested in Bio Farma's cold room, freezer, and walk-in cooler at Politeknik Negeri Bandung to represent various vaccine storage conditions. The results show that the system records data in real-time with a high level of accuracy (temperature error <1%, RH ±15%), low data loss (6 out of 426 data in 10 days), and operating endurance of ±3 hours. Tests proved the system to be an accurate, automated monitoring system for the cold chain vaccine storage.

Interactive Learning for Website-Based PID Controller

2025-09-12T16:22:01+07:00

Conventional learning methods for PID control systems demonstrate weaknesses in concept comprehension effectiveness due to lack of real-time visualization and theory-practice integration. This study aims to develop a web-based interactive learning platform integrating digital simulation with physical experiments using ESP-32. The research method employs Research and Development approach with ADDIE model including literature study, system design, platform implementation, and evaluation through beta testing with 23 Electrical Engineering students. The platform utilizes ESP-32, DC motor, rotary encoder, BTS 7960 driver, and web interface using HTML, Tailwind CSS, and JavaScript for real-time PID parameter control via WebSocket protocol. Evaluation results show average pre-test and post-test score improvement of 34.7% with paired t-test analysis p < 0.01. The platform achieves ±2% measurement accuracy, 45ms communication latency, and 99.2% WebSocket stability. Quality assessment yields feasibility score 4.2/5.0, practicality 4.0/5.0, and effectiveness 4.3/5.0. The platform significantly improves PID control concept understanding compared to conventional methods.

Design of Liquid Organic Fertilizer Composting Automation System with Internet of Things – Based Temperature Sensor

2025-08-07T14:48:56+07:00

Organic waste management is a significant environmental challenge, yet it has the potential to produce valuable products such as liquid organic fertilizer. Conventional composting processes tend to be inefficient and require manual intervention. This study aims to design and implement an automated composting system for liquid organic fertilizer based on the Internet of Things (IoT) using the ESP32 microcontroller, DS18B20 temperature sensor, and actuators including a pump, exhaust fan, and stirring motor. The system is designed with temperature set-point-based control logic, where actuators are automatically activated when the temperature falls below 25 °C or rises above 50 °C. Testing was conducted in two stages: without load and with organic material load. Temperature sensor calibration results showed high accuracy with an average error of 0.08 °C and precision with a standard deviation of 0.2 °C. The system proved capable of operating independently, responding quickly to temperature changes, and integrating with the Ubidots and Telegram platforms for real-time monitoring and notifications. The main contribution of this research is the implementation of a temperature-based automatic control system integrated with IoT, which differs from previous studies that mostly focused only on monitoring functions.

Development of a MEMS-Based Intensitymeter with STA/LTA Event Detection Algorithm and Multi-Channel Alert System

2025-09-09T14:28:23+07:00

Indonesia is an earthquake-prone country due to its location at the convergence of three major tectonic plates. To support disaster mitigation, a reliable and affordable monitoring system is required. This study presents a low-cost intensitymeter using a MEMS WT61C sensor with the STA/LTA detection algorithm, Raspberry Pi 4 for processing, and a Ublox Neo-M8N GNSS module for time and location synchronization. The system supports online and offline modes with a store-and-forward mechanism and delivers alerts via buzzer, SMS, and Telegram. The WT61C was configured with 20 Hz bandwidth and 100 Hz sampling rate. Tests showed the device detected local earthquakes, calculated Peak Ground Acceleration (PGA), and estimated Modified Mercalli Intensity (MMI). In simulations of the Lombok 2018 earthquake (M7.0), it produced PGA values of 0.5704 g (23.3% error) and 0.7495 g (0.8% error) against the reference 0.744 g, both consistent with MMI VIII. SMS was sent serially with 5–7 s latency, while Telegram worked in real time. Validation was limited to a simulator with one dataset, without diverse soil or magnitude scenarios. In conclusion, the system provides an effective, low-cost solution for earthquake intensity monitoring and has potential for early warning applications.

Intelligent Comfort Management in Classrooms Using SSD-Based Occupant Detection and PMV-Guided Environmental Control

2025-08-06T09:20:27+07:00

Room comfort is critical for enhancing productivity, particularly in classrooms. Two key factors are temperature and lighting, governed by ASHRAE 55 for thermal comfort (PMV range of –0.5 to 0.5) and SNI 6197:2020 for classroom lighting (350 lux). This study develops an intelligent system that coordinates occupant detection with temperature and lighting control. Occupant detection was implemented using the Single Shot MultiBox Detector (SSD) with MobileNetV2, a camera as the sensor, and image processing on an NVIDIA Jetson Nano. The detected occupant coordinates were used to control lighting patterns, while temperature was measured with a DHT22 sensor and regulated through PMV-based calculations. The recommended temperature setpoints were transmitted to an air conditioner via an IR blaster controlled by an ESP8266. Experimental results show that the detection system achieved 95% accuracy, 99% precision, 95% recall, and a 97% F1-score at a threshold of 0.3. The lighting control system achieved a MAPE of 14.49%, while the temperature control system achieved a MAPE of 4.53% with an average MAE of 1.1 °C. These findings demonstrate that the proposed system effectively integrates occupant detection with automated temperature and lighting control, ensuring improved classroom comfort.

Design of Process Control System for Cocoa Bean Drying Equipment

2025-09-09T14:46:04+07:00

The growth in cocoa production in Indonesia is not matched by its quality, where the drying process is a crucial parameter that must be controlled. Excessively high drying temperatures tend to negatively impact the beans, resulting in a sour aroma, and the beans can become charred. The moisture content in cocoa beans needs to be reduced to a maximum of 7.5% to produce quality cocoa beans. This research developed the creation of a cocoa bean drying box with a drying process control system, temperature and humidity monitoring by the SHT20 sensor. There is a DS18B20 sensor to measure the temperature of the cocoa beans during drying. Two microcontrollers are used: STM32 as a control and displays sensor readings on the LCD, and ESP32 connected to the STM32 to send data to the dashboard and database. The drying process utilizes a heater as a heating element until the temperature reading on the SHT20 sensor is ≤ 55°C. When the heater is inactive, a fan will be active to lower the drying temperature to maintain the drying process at an optimal temperature and prevent damage to the cocoa beans. The results of testing the cocoa bean drying process for 24 hours with data collection every 1 hour, where real-time data is stored in the online dashboard, obtained the average temperature of the drying box room is 51°C, the average temperature of the cocoa beans is 42°C, and the average moisture content of the cocoa beans is 7.5%.

Dissolved Oxygen Monitoring and Control System IoT-Based Brackish Water Vannamei Shrimp Farming Using Long Range Wide Area Network (LoRaWAN)

2025-08-15T09:07:55+07:00

Vannamei shrimp farming in Indonesia is increasing due to its high economic value. Water quality management in aquaculture ponds is crucial to minimize the number of diseases related to poor water quality. One of the water quality parameters in shrimp farming is dissolved oxygen. In this monitoring and control system for dissolved oxygen in brackish water Vannamei shrimp farming based on the Internet of Things (IoT) using the Long Range Wide Area Network (LoRaWAN), measurements of dissolved oxygen levels in cultured water are carried out and displayed in the Android application so that it can be monitored by farmers in real time. When the dissolved oxygen level in the cultured water is more than 5.7 mg/l, the aerator will be OFF, but if the dissolved oxygen level is less than 5.7 mg/l, the aerator will be ON to maintain optimum dissolved oxygen levels for shrimp farming, which is more than 5 mg/l. Dissolved oxygen sensor validation is carried out, resulting in a measurement error correction value of 2.25% and an accuracy level of 97.74%. Based on the test results, this device can monitor dissolved oxygen in real time and operate the control system to maintain levels above the predetermined setpoint of 5 mg/l.

Development of a Portable Coffee Bean Moisture and Temperature Meter Using a Capacitive Sensor and Real-Time Data Storage

2025-09-09T14:07:28+07:00

The primary quality indicator of coffee beans is determined by their moisture content. This study aims to develop a portable prototype device for measuring both the moisture content and temperature of coffee beans, utilizing an ESP32 microcontroller integrated with a Capacitive Soil Moisture Sensor v1.0 and an SHT21 sensor. The device is designed to provide accurate and efficient measurements, with results displayed in real time on an OLED screen. In addition, the system stores measurement data on an SD card for further analysis. Experimental testing was conducted five times for each sample, comparing the results of the prototype with reference instruments, namely the YL-69 sensor for moisture measurement and a digital thermometer for temperature measurement. The results demonstrated that the device achieved a high level of accuracy, with an average relative error of 1.05% for moisture content and 0.91% for temperature. Furthermore, the prototype was proven to be portable and energy-efficient, consuming 7.7 Wh over 1.1 hours of operation, as evaluated through battery-based performance testing until full discharge. With its integrated data storage and real-time monitoring capabilities, this device provides a practical solution for coffee farmers and processors in maintaining and ensuring the quality of coffee beans.