Jurnal Otomasi Kontrol dan Instrumentasi

Proportional-Controlled Microclimate Incubation System with IoT Monitoring for Dendrobium Seedling Acclimatization

Al Barra Harahap — 2026-07-02

Dendrobium orchid seedlings transferred from in vitro culture require stable microclimate conditions during acclimatization, particularly temperature, humidity, and photoperiod regulation, to improve adaptation to non-aseptic environments. However, quantitative evaluations of laboratory-scale incubation systems under constrained actuation conditions remain limited. This study presents a compact microclimate incubation system implementing proportional-only temperature control using fan-based unidirectional cooling, scheduled irrigation and lighting, and real-time IoT monitoring through a Node-RED dashboard. The system was developed using an ESP32-S3 controller and DHT22 sensors in a semi-enclosed multi-tier rack with a capacity of 360 seedling pots. Sensor calibration showed strong agreement with a reference instrument, achieving R² > 0.99 for temperature and humidity measurements. Temperature regulation at a reference value of 29.3 °C achieved a steady-state mean absolute error of 0.1 °C within a deviation range of −0.5 to +0.1 °C during 572 minutes of continuous operation, while maintaining all measurements within ±2 °C of the thermal tolerance range for Dendrobium acclimatization. Increasing proportional gain from = 1000 to 2550 reduced the reference entry time from 362 s to 208 s. These findings demonstrate that proportional-only control with constrained cooling actuation can provide stable temperature regulation for compact indoor incubation systems.

Design and Development of a Low-Cost IoT-Based Portable Pulse Oximeter

Indri Desriani — 2026-07-23

Real-time monitoring of heart rate and oxygen saturation is commonly performed using conventional medical devices that are impractical for daily use. This study aims to design a low-cost, Internet of Things (IoT)-based portable pulse oximeter prototype for real-time health monitoring. The system employs a MAX30100 sensor to measure BPM and SpO₂, an ESP32 microcontroller for data processing, and an OLED to display the results. The measured data are also transmitted to the Blynk application for remote smartphone monitoring. Performance was evaluated on 20 participants consisting of 10 men and 10 women, by comparing the measurement results with those of the commercial Serenity OX-48 pulse oximeter. System performance was assessed using accuracy, Mean Absolute Error (MAE), standard deviation, and Pearson correlation. The male group achieved an average accuracy of 98.71% for BPM (MAE = 1.09 BPM; r = 0.99) and 99.16% for SpO₂ (MAE = 0.80%; r = 0.92). Meanwhile, the female group achieved an average accuracy of 98.88% for BPM (MAE = 1.01 BPM; r = 0.99) and 99.17% for SpO₂ (MAE = 0.80%). These results indicate that the system delivers accurate, stable, and reliable measurements and is suitable for real-time IoT-based physiological monitoring.

Design and Development of a Low-Cost Automated Guided Vehicle (AGV) Prototype based on a Microcontroller for Internal Material Distribution in Industrial Small and Medium-Enterprises (SMEs)

Yudha Hamdi Arzi — 2026-08-10

Small and medium-sized enterprises (SMEs) require internal material distribution systems that are efficient, safe, maintainable, and affordable. This study aims to design and test a low-cost microcontroller-based Automated Guided Vehicle (AGV) prototype for internal material distribution in SMEs. The system uses a differential drive configuration, BLDC motor driver, magnetic path navigation, Roboteq MGS1600 magnetic sensor, RPLIDAR C1, ESP32-C3, limit switches, emergency stop, modular battery, and STM32-based PCB control board. The research method includes requirement identification, design formulation, mechanical and electronic design, control software development, system integration, and functional testing. The results show that the magnetic sensor detected magnetic tape up to 3.0 cm. The obstacle detection system produced stopping-distance MAE values of 4.02 cm for human obstacles and 9.39 cm for object obstacles relative to the 30 cm setpoint. Motor-driver characterisation showed an effective PWM duty cycle range of 31-70%, with a saturation speed of about 283 RPM. The AGV prototype also towed approximately 403 kg on a flat track. These results indicate that the proposed AGV can serve as an economical initial alternative for material handling automation in SMEs.

Pressure Control System for the Production of Salted Duck Eggs Utilizing Constant and Pulsed Pressure Techniques

Nina Zelika Fitri — 2026-08-13

Duck eggs (Anas javanica) are highly nutritious but prone to spoilage, making preservation methods such as salting necessary. However, traditional egg salting requires a relatively long processing time of approximately 10–14 days, making it less efficient for mass production. Consequently, a technology that can accelerate the salting process while maintaining an acceptable product quality is required. This study proposes an automatic egg salting system based on the principle of osmotic dehydration, employing two pressure modes: constant and pulsed. In the pulsed pressure mode, the salting process consisted of repeated cycles: a 7.5 min pressure phase, followed by a 15 min relaxation phase, whereas in the constant pressure mode, the pressure was maintained continuously throughout the salting process. The resulting products were evaluated for their salt content using the Mohr method, and sensory qualities were assessed through organoleptic tests. The results showed that in the constant-pressure mode, increasing the pressure from 1 to 2 bar over a 2-day processing period increased the salt content from 0.95% to 1.33%. Meanwhile, the pulsed pressure mode accelerated the salting process, achieving a salt content of 1.11% at 1 bar and 1.62% at 2 bars, approaching the results of traditional 10-day salting.

IoT Based Electrical Energy Consumption Monitoring System Design

Ayub Abdullah — 2026-09-04

Conventional kWh meters have a functional limitation: they measure household electrical energy consumption without the ability to control electrical loads, which can lead to uncontrolled energy use and high electricity costs. This study aims to design and build an Internet of Things (IoT)-based energy monitoring system capable of tracking electrical parameters in real time while automatically and remotely controlling electrical loads. The novelty of this research lies in the variation of testing time, the type and capacity of loads used, and the evaluation of the system's energy-saving effectiveness under energy-limiting control. The system was evaluated using an error percentage calculation method, with a Taffware KWE-PM01 wattmeter as the comparison standard, the 5V Songle relay datasheet, and efficiency savings calculations. Results show that the PZEM-004T sensor's measurement error percentage remained below the ±5% tolerance limit, with a maximum error of 4.3%. Relay response time ranged from 0.2 to 1.3 seconds, and the system improved electrical energy efficiency by 31.01% for LED lamp loads and 30.83% for electric fan loads by setting a daily energy consumption limit for each load. Overall, the designed system proved reliable in terms of measurement accuracy, relay response time, and energy-saving efficiency.

Predictive Modeling Based on Aspen HYSYS for Rhodinol Content Estimation in Pilot-Scale Vacuum Fractional Distillation of Citronella Oil: Agreement Evaluation with Experimental Data

Fadli Hastito — 2026-10-02

Citronella oil is an essential oil widely used in the perfume, cosmetic, pharmaceutical, and natural-product industries owing to its high-value rhodinol content (citronellol and geraniol). This study aims to develop and evaluate a vacuum fractional distillation process model based on Aspen HYSYS software to predictive the relative rhodinol content of citronella oil and evaluate its agreement with the actual pilot-scale process. Feedstock characterization used GCMS and physicochemical testing. Modeling was performed by varying vacuum pressure, reboiler temperature, and reflux ratio to determine operating conditions tested on a pilot-scale vacuum fractional distillation unit through three experiments, comparing the relative rhodinol content from the model and experiments based on percentage error. Results show the third experiment produced the highest relative rhodinol content of 66.51% at 26 mbar, a reboiler temperature of 134°C, and a reflux ratio of 6:1, with prediction error ranging from 25.01% to 42.80% and the lowest error in the third experiment. These findings indicate the Aspen HYSYS model provides a predictive trend supporting the design of operating conditions but still shows deviation from actual pilot-scale conditions, indicating the need to refine model parameters, operating conditions, and process assumptions to improve model reliability for larger-scale process development.

Design and Development of an O-SEATER Simulation Platform for the BRIN Operational Area Using NVIDIA Isaac Sim

Rifki Rochiman — 2026-10-08

Developing algorithms for mobile robot systems requires a simulation environment that models operational conditions. This research develops a simulation platform for the O-SEATER autonomous vehicle in the virtual environment of BRIN KST Samaun Samadikun using NVIDIA Isaac Sim. The virtual model was connected to the physical vehicle via a wireless network using the Robot Operating System 2 (ROS 2) for Hardware-in-the-Loop (HIL) and rosbag playback tests. The playback replicated the actual movements perfectly, with a Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of 0.0000 and an ideal Real-Time Factor (RTF) of 1.0010. HIL simulation ran 1.81 times slower (RTF = 0.5518), with a memory spike of 27.1 GiB, 214.63 ms network latency, and 15% packet loss. To compensate for this temporal deviation, we applied Dynamic Time Warping (DTW), resulting in high-precision HIL tracking (Linear X MAE = 0.0299 m/s; Angular Z MAE = 0.0224 rad/s). The high communication latency is an architectural limitation. Nevertheless, we achieved interactive communication and generated virtual sensor data (RGB and IMU). This platform remains a sufficiently valid algorithm-testing medium and the basis of the O-SEATER Digital Twin system.

Data-Driven Prognostics of LiFePO4 Battery Remaining Useful Life in Residential Microgrids: A Hybrid Approach Integrating Recursive Least Squares and Long Short-Term Memory

Zaenal Abidin — 2026-10-16

The growing use of residential photovoltaic systems is increasing the deployment of Lithium Iron Phosphate (LiFePO₄) battery energy storage systems. However, dynamic load demands and frequent cycling accelerate battery degradation. Accurate state-of-health estimation and remaining useful life prediction are critical for operational reliability. This study introduces a hybrid framework that integrates recursive least squares with a long short-term memory network. A first-order Thevenin equivalent circuit model is used to extract physical parameters such as ohmic resistance, polarization resistance, and polarization capacitance. The recursive least squares algorithm, with a forgetting factor of 0.999, adaptively tracks resistance-based State of Health, detecting an increase in ohmic resistance from 26.5 to 37.04 milliohms after 348 cycles. This approach achieves a root-mean-square error of 1.0554% and a coefficient of determination of 0.8354. These parameters are then used to train the long short-term memory network to model degradation trends. The network predicts remaining useful life with a root mean square error of 0.8947% and a coefficient of determination of 0.9553, forecasting lifespans of 511, 953, and 1,310 days for end-of-life thresholds of 80%, 70%, and 60% State of Health, respectively.

Autofilling: An Automatic Water Filling System Based on Load Cell and Takagi–Sugeno Fuzzy Control with Real-Time Monitoring on Arduino

Ferhad Zulfas — 2026-10-17

The automatic water filling process requires high accuracy to ensure that the filled amount meets the specified target. Systems operating at a constant pump speed tend to produce overshoot because the flow rate cannot be adjusted as the target is approached. This study develops an Autofilling system based on weight feedback using Takagi-Sugeno fuzzy logic control to adaptively regulate the pump speed. The system integrates an Arduino Nano, a load cell with an HX711 module, a PWM-controlled DC pump, a solenoid valve, and a Nextion HMI for real-time monitoring. The fuzzy controller uses error and delta error as inputs to determine the pump PWM. Tests were conducted at target weights ranging from 200 to 1000 g by comparing the system without fuzzy control with the Takagi-Sugeno fuzzy-controlled system. The fuzzy controller reduced the average error from 23.24 g to 1.20 g and the percentage error from 5.53% to 0.21%, while increasing the accuracy from 94.47% to 99.79%. The average filling duration was also reduced from 44.61 s to 22.08 s. These results demonstrate that Takagi-Sugeno fuzzy control improves accuracy and reduces overshoot, with a shorter filling duration under the experimental configuration used.

Mitigation of Single Point of Failure Risk in Multifuel Boiler through Implementation of Double Channel Digital Input for RUN PAF Indication

M Dicky Alfansyah — 2026-10-19

The Primary Air Fan (PAF) is critical equipment in a multifuel boiler, and its RUN status is used for permissive and interlock functions in the Distributed Control System (DCS). The existing configuration used a single channel digital input, creating a potential single point of failure if the receiving channel failed. This study proposes a preventive improvement using double channel digital input with OR (1oo2) logic. The method consisted of field observation, evaluation of the existing configuration, wiring and Function Block Diagram (FBD) design, implementation, and functional verification. Verification covered 14 conditions: four loop tests, four simulation tests, two failover tests, and four permissive/interlock checks. All 14 conditions met the defined functional criteria, giving a 100% functional test success rate. In both failover tests, CAL RUN PAF remained active when one input channel was disabled while the other still indicated RUN. The result demonstrates that the preventive improvement maintained the RUN PAF indication under the individual channel-failure conditions tested. The implementation is limited to the DCS terminal and digital input side, while the field signal source and cable remain single-path. Thus, the result demonstrates functional mitigation of the tested failure condition, not a quantified reliability or availability improvement.

Development and Experimental Evaluation of a Smartphone-Based Mixed Reality Gun Simulator

Victor Sinaga — 2026-10-20

Mixed Reality (MR) has gained increasing attention in simulation and training because it enables immersive interaction between virtual and physical environments. However, many existing MR systems rely on expensive head-mounted displays and dedicated tracking hardware, limiting their accessibility for educational and proof-of-concept research. This study aims to develop and experimentally evaluate a low-cost smartphone-based MR gun simulator operating in Virtual Reality (VR) and Augmented Reality (AR) modes. Its novelty lies in integrating consumer-grade hardware into a unified MR platform that supports immersive interaction at an affordable cost. The prototype integrates a smartphone, a custom handheld controller, embedded sensing, computer vision, and a real-time simulation environment. Experimental evaluation examined crosshair mapping accuracy, response latency, system frame rate performance, and AR object detection reliability. Results show that the prototype achieved acceptable interaction accuracy, responsive real-time performance, stable rendering in both VR and AR modes, and reliable object detection throughout the evaluation. These findings demonstrate that affordable smartphone-based MR systems can provide sufficient performance for proof-of-concept research and educational applications, establishing a practical foundation for developing immersive training and human-computer interaction systems.

Development of a CO Gas Detection Device in a Car Cabin Based on ESP32 and MQ-7 Sensor

Fikri Bangun Nugraha — 2026-10-21

Carbon monoxide (CO) is an invisible, odorless toxic gas that human senses cannot easily identify on their own. Inside a vehicle cabin, exposure to this gas may threaten occupant health, especially when dense traffic conditions allow exhaust emissions to build up. This work focuses on designing and building a cabin-based CO monitoring device that relies on an ESP32 microcontroller together with an MQ-7 sensor, combined with visual, audio, and haptic alerts. A Research and Development (R&D) method following the 4D model guided the project. Two testing phases were carried out: assessing the device's response and evaluating its on-vehicle performance across normal and simulated-congestion scenarios. Findings show an average detection time of 26.46 seconds, a notification-activation time of 5.32 seconds, and a sensor reading delay of 2.79 seconds. During performance testing, CO levels reached 9.9 ppm in normal conditions and climbed to 20.5 ppm under simulated congestion. Overall, the device can track rising CO concentrations in real time and issue early warnings to vehicle occupants.

FPGA-Based Fuzzy-PID Hybrid Control for Electric Oven Temperature

Yurixa Sakhinatul Putri — 2026-10-21

Resistive electric ovens exhibit high thermal inertia and nonlinear dynamics, making fixed-parameter PID controllers prone to overshoot and slow responses under varying setpoints. This study proposes and implements a Hybrid Fuzzy-PID controller on a Cyclone IV FPGA using a zero-order Takagi-Sugeno fuzzy inference system as a real-time auto-tuner for the Kp and Ki parameters. The controller is evaluated against a conventional PID controller tuned using the Ziegler-Nichols method. The fuzzy inference system uses error and delta error as inputs to adapt the controller parameters according to changes in the thermal response of the oven. All control algorithms are implemented in VHDL on a Cyclone IV FPGA without floating-point operations. Experimental results demonstrate that the proposed Hybrid Fuzzy-PID controller provides improved thermal response compared with the conventional PID controller, achieving faster settling behavior, controlled overshoot, and lower average power consumption under the tested conditions. The FPGA-based implementation also provides more accurate and deterministic actuation than the microcontroller-based implementation. These findings demonstrate that the proposed FPGA-based Hybrid Fuzzy-PID controller can improve real-time temperature regulation and power utilization in resistive electric ovens.

Effect of Camera Type on Drone Detection Performance and UAV Control Response Based on YOLOv8 and YOLOv11

Nesha Roswanda Sakhdiah — 2026-10-24

The development of Unmanned Aerial Vehicle (UAV) technology requires drone detection systems that are accurate, fast, and capable of operating in real time. This study analyzes the effect of camera characteristics on drone detection performance and UAV control response using YOLOv8 and YOLOv11. Experimental testing was conducted using five cameras with 720p and 1080p resolutions at distances of 1–5 m, with real-time inference performed using a MacBook Air M1. Distance estimation was performed using a monocular distance estimation approach based on the drone’s bounding box height, object height, and camera focal length. The evaluation parameters included detected distance, MAE, RMSE, FPS, roll and pitch control values, and left and right elevon angles. The results show that camera characteristics affect distance estimation accuracy, detection speed, and UAV control output. YOLOv11 with Logitech BCC950 achieved an MAE of 0.34 m and RMSE of 0.39 m, but had low FPS. Logitech HD720P achieved 15.8 FPS with an MAE of 0.38 m and RMSE of 0.43 m.