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The problem lies in the load lock from the wheel arm, the BLDC motor whose distance cannot be adjusted, and the flywheel whose movement is less smooth than the original design. The purpose of refining the design is to obtain smooth movement and the position of the load lock from the wheel arm, the BLDC motor that can be adjusted to be ergonomic and optimal. The method of refining the design and manufacture of the rear shock breaker spring type electric bicycle through the stages of working load analysis, the need for the distance of the load setting position and the BLDC motor, calculating the construction strength, manufacturing components, assembling components, and evaluating the results of the shock breaker manufacture. The results of refining the design and manufacture of the rear shock breaker spring type electric bicycle show that the movement of the load lock position from the wheel arm and the BLDC motor is smooth, the flywheel must be balanced, the dimensions of the shock breaker device are 120 cm long, 49.5 cm wide, 155 cm high, 120 rpm rotation speed, 2 cm shock breaker movement distance, and 1.5 cm sideways movement deviation which implies being able to provide adequate damping for electric bicycle riders well.

This study aims to design, implement, and test a prototype that automates three functions, namely watering, fertilizing, and pest control based on Arduino Uno with the ability to directly monitor soil moisture and pH. This system is equipped with four main types of sensors. Soil condition monitoring involves an FC-28 soil moisture sensor and a soil pH sensor, water level measurement involves an HC-SR04 ultrasonic sensor, and pest detection in the plant area involves a RIP sensor. All data obtained from these sensors is then processed by the Arduino Uno microcontroller to automatically activate actuators such as water pumps, liquid fertilizer pumps, buzzers, and DC motors according to soil conditions and plant needs. Prototype testing was conducted on simulated land with various scenarios of moisture, soil pH, and pest activity. The test results revealed that the system was proven to be able to significantly optimize water and fertilizer utilization, as well as reduce pest disturbances that could potentially damage plants.  In addition, this system also displays the operational status directly through an LCD screen, making it easy for users to monitor. The advantage of this system is its multi-function integration in a single device that is cost-effective and easy to operate. In the future, the functionality of this system can be improved through integration with Internet of Things (IoT) technology, enabling remote monitoring and control with greater efficiency. More broadly, this study is expected to support increased production and sustainable agricultural practices in Indonesia.

Manual post-harvest paddy stirring requires significant time and labor and often results in uneven mixing, which can affect grain quality. To address this issue, this study designed and implemented a prototype of an Internet of Things (IoT)-based paddy stirring robot to simplify the process and improve efficiency. The system utilizes an ESP32 microcontroller as the main controller, DC motors as the stirring mechanism, and an IoT module for wireless connectivity to a mobile application. The research stages included hardware design, control system programming, IoT platform integration, and performance testing. Testing was conducted to evaluate response time, mixing uniformity, and power consumption. The results showed that the system could be operated remotely via a local Wi-Fi network with an average delay of less than 1 second, enabling real-time control. The prototype successfully stirred 0.3 kg of paddy with a mixing uniformity rate of 92% and an average power consumption of 12 watts. The application of IoT in the paddy stirring mechanism significantly improved time efficiency, reduced manual labor requirements, and maintained grain quality compared to traditional methods. These findings indicate the potential for further development into a large-scale automated paddy processing system with integrated humidity and temperature sensors for real-time quality monitoring, supporting the modernization of post-harvest processing through digital technology.

The DC motor serves as the main drive of the vessel and is equipped with a rotary encoder that functions to regulate the movement of the sensor in measuring sediment levels. This rotary encoder is also used to monitor and represent the rotational speed of the DC motor. System testing was carried out by implementing a Fuzzy Logic Controller (FLC) algorithm to control the DC motor speed in moving the vessel, ensuring stable motion. This fuzzy logic–based approach is expected to improve accuracy and efficiency in sediment volume calculations, while also reducing potential errors that commonly occur in manual methods. Simulating motor speed control using the fuzzy logic algorithm in MATLAB, the best test results were achieved over several trials, with a rise time of 376.310 ms and an overshoot of 83.33%. Motor speed measurements using both a tachometer and Arduino produced consistent results, with an average relative error of 0.18%.

This research presents the design, development, and implementation of a mini smart car prototype that operates using Internet of Things (IoT) technology. The system is built around the ESP8266 microcontroller (Amica version), which functions as the core processing unit responsible for handling Wi-Fi communication and data processing. The motion of the car is controlled by an L298 motor driver module that regulates the operation of DC motors. The entire system is powered by a 3.7-volt rechargeable battery, ensuring portability and energy efficiency. The study discusses in detail the hardware configuration, software programming, and integration of IoT-based control through a web or mobile interface. Functional testing of the prototype, named MINIOT, focuses on evaluating the responsiveness, stability, and reliability of remote control operations. The results are expected to show that the system can effectively receive and execute user commands while transmitting real-time telemetry data, such as motor status and connection indicators. This project demonstrates the feasibility of low-cost IoT-based automation for small-scale robotic applications.

This research presents the design, development, and implementation of a mini smart car prototype that operates using Internet of Things (IoT) technology. The system is built around the ESP8266 microcontroller (Amica version), which functions as the core processing unit responsible for handling Wi-Fi communication and data processing. The motion of the car is controlled by an L298 motor driver module that regulates the operation of DC motors. The entire system is powered by a 3.7-volt rechargeable battery, ensuring portability and energy efficiency. The study discusses in detail the hardware configuration, software programming, and integration of IoT-based control through a web or mobile interface. Functional testing of the prototype, named MINIOT, focuses on evaluating the responsiveness, stability, and reliability of remote control operations. The results are expected to show that the system can effectively receive and execute user commands while transmitting real-time telemetry data, such as motor status and connection indicators. This project demonstrates the feasibility of low-cost IoT-based automation for small-scale robotic applications.

Air pollution and oil reserves are two major issues in the technological development of the automotive industry. Air pollution is caused by gases from burning fossil fuel vehicles. In 2018-2019 Indonesia experienced a drastic decrease in petroleum resources by 49.8%. To overcome this problem, many researchers have conducted research on electric vehicles, including electric bicycles. This study aims to determine the effect of distance and load on BLDC motor power consumption on a prototype e-bomber electric bicycle designed for all terrains such as rocky, sandy, and muddy, and has a large battery capacity, low power consumption, and an electric motor with good speed and torque. This research uses a pseudo-experimental method with a quantitative approach. Tests were carried out on e-bomber electric bicycles with distances of 3 km, 5 km, and 8 km and loads of 60 kg, 70 kg, and 80 kg with a speed of 25 km / h. The results showed that there was an influence of distance and load on the e-bomber electric bicycle. The results showed that there was an effect of distance and load on BLDC motor power consumption with the results of graph analysis and two-way ANOVA tests conducted and the lowest average power consumption of 500 watts at a distance of 3 km and a load of 60 kg, while the highest average power consumption was 522.5 watts at a distance of 8 km and a load of 80 kg.

Blood transfusion is a critical medical procedure that requires the blood to be at a temperature close to normal human body temperature, approximately 36– 38°C. Transfusing cold blood can lead to serious complications such as hypothermia, coagulation disorders, and even cardiac arrest. Therefore, a reliable and automated blood warming device is essential to ensure safe transfusions. This study aims to design and modify a Blood Warmer Thawing device based on the Arduino Uno microcontroller as an innovative and cost- effective solution, particularly for healthcare facilities with limited resources. The system integrates a DS18B20 temperature sensor to monitor the temperature of the heating medium in real time, with data displayed on a 20x4 I2C LCD. Users can set the desired temperature via a 4x4 keypad, and the system automatically adjusts the heater performance based on the detected temperature. To enhance safety and operational efficiency, the device is also equipped with a buzzer as a warning indicator when the temperature exceeds the safe threshold, and utilizes a DC motor and cooling fan to maintain proper heat circulation. Test results indicate that the device is capable of maintaining the liquid temperature within the ideal range for blood transfusions, with high stability and fast response to temperature changes. This innovation offers a practical, affordable, and easy-to-implement solution to support effective and safe blood transfusion procedures in various healthcare settings.

The need for environmentally friendly marine transportation continues to increase, especially in tourist areas such as Penyengat Island, Tanjungpinang, Riau Islands. In the local context, the design of electric boats has not been widely developed for small islands in Indonesia, even though the potential and urgency for its application is very high. Geographical constraints, limited charging infrastructure, and a lack of technical data are the main obstacles. This research focuses on the design and construction of an electric-powered tourist boat prototype with an asymmetrical catamaran hull type as an effort to support a sustainable transportation system. The boat design applies an asymmetrical catamaran hull configuration to improve sailing stability and energy efficiency. The propulsion system is controlled via a wireless PS2 joystick integrated with an ESP32 microcontroller, supported by a 24V DC motor powered by lithium-ion batteries and solar panels as a supplement. Test results show that the boat can operate stably with remote control, good energy efficiency, and zero emissions during operation. Some technical challenges encountered include limited operational duration due to battery capacity and high sensitivity of electronic components to water exposure. Overall, this prototype has great potential for further development as an environmentally friendly alternative for maritime transportation system. The stable catamaran hull design provides advantages in terms of comfort and safety, especially in calm or shallow waters. The electric propulsion system used has proven to be efficient and responsive, supported by a remote control mechanism that is easy to operate via a wireless joystick

The rise in motor vehicle theft cases in various regions indicates the weakness of the security systems implemented by most users. Systems such as manual locks and alarms often fail to prevent crime, either because they are easily hacked conventionally or due to user negligence in their operation. In today's technological era, a system is needed that is not only secure, but also intelligent and practical. One promising solution is the implementation of a facial recognition-based security system. This study aims to design and test a vehicle security simulation system using facial recognition technology integrated with Arduino Uno and MATLAB. This system utilizes a laptop camera to capture the user's facial image, then performs a detection and verification process using the FaceNet algorithm. If the face is recognized and verified with data stored in the database, the Arduino will activate the actuator components in the form of a DC motor to simulate starting the engine, and a servo motor to simulate opening the vehicle door. This study uses a quantitative experimental approach to analyze the effect of variations in distance (30, 40, and 50 cm) and lighting brightness levels (10–20, 21–30, and 31–40 lux) on the system's response time. A total of 27 combinations of conditions were tested, and the data obtained were analyzed using Microsoft Excel and ANOVA tests in Minitab software. The results of the analysis showed that the optimal response time was obtained at a distance of 40 cm with a medium level of illumination (21–30 lux). In addition, both distance, brightness, and the interaction between the two factors were shown to have a significant effect on the system's response time (P-Value < 0.05). These findings indicate that the system is quite sensitive to environmental changes, so further testing is highly recommended, especially to measure the actual delay, the detection error rate, and the development of a more robust face detection algorithm so that the system can be used reliably in various lighting conditions and face capture angles in the real world.

This study focuses on the development of an interactive web-based learning platform for Proportional-Integral-Derivative (PID) control systems, aimed at addressing the conceptual challenges faced by electrical engineering students when learning PID through conventional teaching methods. Despite its foundational role in control theory, PID remains difficult to grasp without practical visualization and hands-on experimentation. To bridge this gap, the research introduces a practical and accessible platform that enhances conceptual understanding through real-time simulations and physical interaction. The proposed system integrates key hardware components including an ESP-32 microcontroller, DC motor, rotary encoder, BTS 7960 motor driver, and I2C LCD. The platform’s web interface is built using HTML, Tailwind CSS, and JavaScript, enabling intuitive user interaction. Motor response data is captured via the ESP-32 and transmitted to the web interface using the WebSocket protocol, allowing users to instantly visualize system behavior as PID parameters (Kp, Ki, Kd) are adjusted. This dynamic feedback mechanism enables students to observe changes in system characteristics such as rise time, overshoot, and settling time in real time. To evaluate the platform’s feasibility, practicality, and educational effectiveness, beta testing was conducted among electrical engineering students using Likert-scale questionnaires. The results demonstrated that users were able to successfully interpret the impact of PID tuning on system performance. The average evaluation score reached 75.13%, indicating strong agreement regarding the platform’s educational value and its effectiveness in enhancing learning outcomes. In conclusion, the study affirms that the developed web-based platform offers a feasible, engaging, and pedagogically effective alternative to traditional learning approaches. By combining interactive simulations with physical experimentation, the platform significantly improves students’ understanding of PID control systems.

The rapid growth of motor vehicles, exceeding 169 million units in Indonesia by 2025, highlights the urgent need for energy-efficient and environmentally friendly transportation solutions, such as hybrid vehicles. Brushless Direct Current (BLDC) motors are crucial components in these systems due to their high efficiency and compact design, particularly when directly integrated into wheels. This study specifically aims to analyze the impact of varying loads on the power consumption of a BLDC motor within a front-wheel-drive hybrid motorcycle prototype equipped with a Continuously Variable Transmission (CVT) system. Experimental data was collected using a wattmeter on a prototype subjected to different passenger loads: 55 kg, 75 kg, and 100 kg, at constant speeds of 20 and 40 km/h. The findings consistently show that an increase in load significantly and positively correlates with higher power consumption of the BLDC motor. For instance, at 40 km/h, power consumption for a 100 kg load reached 729.578 Watt, whereas for a 55 kg load it was 649.605 Watt. This demonstrates that greater effort (power) is required from the motor to overcome the inertia and increased resistance associated with heavier loads. These results contribute to optimizing energy efficiency in hybrid vehicle design and underscore the importance of load management for sustainable transportation.

The PG45 DC motor is a drive system used on sediment detection boat. To achieve the desired stability and speed, it is necessary to apply a control system to the sediment detection boat drive system. Control systems need to be tuned to ensure that they function properly and are responsive to changes. In order to complement the previous research, further research was carried out focusing on determining the PID control parameters on the angular speed of the PG45 DC Motor using Simulink. The PG45 DC motor works based on the Arduino programming algorithm that has been designed so that it can rotate at a predetermined speed. This research modeled the sediment detection ship system on Simulink with a similarity rate of 94.09%. The results of this study indicate that the tuning method used, namely trial and error, produces good control on the sediment detection ship system model that has been assembled in Simulink with the value of Kp = 100; Ki = 5; Kd = 15 obtained the value of rise time = 0.2474 seconds and settling time = 0.4104 seconds and overshoot = 0.2175%%.

The development of technology in the field of fisheries is very rapid along with facilitating human work in the field. Human work can be done by tools such as feeding catfish in ponds automatically. This job is easy to do, but problems will arise when catfish are not fed at night or are fed too late, then the catfish will eat smaller catfish so that it can be detrimental to catfish farming owners. With this background, the author created a "Catfish Feeding Control System Based on the Internet of Things (IoT) Using the Fuzzy Sugeno Method". This testing and discussion was carried out by functionally testing each component, testing the program using simulation and testing it as a whole. The results of testing the tool and taking data are expected to obtain valid data and the tool works according to its function and purpose as expected. From the results of the analysis and discussion of the research entitled "Internet Of Things (IoT) Based Catfish Feeding Control System Using the Fuzzy Sugeno Method" it can be concluded as a process of automatic fish feeding using the RTC module as a reference for catfish time three times a day with good results and the process of calculating the amount of fish feed 3 to 8% with fish weight from LOW to HIGH using Fuzzy Sugeno has worked well compared to the results of the BLYNK application.

Worldwide trade is conducted 80% through maritime routes, including the export and import of coal. Coal is a non-renewable energy source, often used as fuel for power plants. As technology advances, detecting metal contaminants in coal cargo becomes crucial to prevent contamination of coal with metal materials. This study aims to (1) understand the operation of a conveyor in transporting coal, and (2) assess how the Proximity inductive sensor detects metal presence. The methods used in this research include real data analysis and literature review, conducted aboard the ship. The researcher designed and developed a prototype system for this purpose. The Proximity inductive sensor is utilized to detect metal contaminants, such as aluminum, iron, and stainless steel, among the coal cargo. The research was carried out during sea practice (prola) aboard the WHS ISKANDAR 1. The findings indicate that the conveyor is driven by a DC motor, and the Proximity inductive sensor effectively detects metals to separate them from the coal cargo, thus purifying the coal from metal contaminants.

The development of electric propulsion systems has become a major focus in efforts to provide energy-efficient and environmentally friendly air propulsion technology. One emerging innovation is the electric motor-based turbojet fan, which is expected to replace conventional fossil-fueled systems. As the need for energy efficiency increases, studies on electrical power consumption and airflow performance are crucial in supporting the development of new-generation propulsion systems. This study aims to evaluate the relationship between nozzle angle and the characteristics of electrical power consumption and airflow velocity in a double-spool turbojet fan. The method used is an experimental test with an ESP32-based control system. The duty cycle is set at 80% to maintain operational stability. Research data is obtained through measurements of electrical current, voltage, and airflow velocity. The nozzle angle variations tested include 13°, 19°, and 25°. The test results show a significant difference between nozzle angle variations on electrical power consumption and wind speed performance. The 13° nozzle angle produces the highest electrical power consumption, indicating a greater energy requirement to maintain airflow. Conversely, the optimal wind speed was found at an angle of 19°, indicating a balance between energy efficiency and aerodynamic performance. Meanwhile, an angle of 25° showed a decrease in performance in terms of both power and speed, making it less effective. In conclusion, the nozzle configuration has a direct influence on energy consumption and fluid dynamics in electric turbojet fan systems. This research provides an important contribution to the design of electric-based propulsion systems by emphasizing efficiency and performance aspects, while supporting the transition to environmentally friendly technologies.

Blood pressure is a crucial factor in the circulatory system of the human body. It refers to the amount of force exerted by the blood on the inner walls of the arteries when it is pumped throughout the circulatory system. Blood pressure can be measured using a device known as a digital sphygmomanometer, which determines systolic pressure, diastolic pressure, and beats per minute (BPM) of the human heart. As technology evolves, the digital sphygmomanometer has been enhanced with features such as the Internet of Things (IoT). IoT in healthcare refers to the use of information technology to enable remote health monitoring by healthcare professionals. A digital sphygmomanometer equipped with IoT facilitates the exchange of diagnostic information, treatment decisions, and prevention of diseases and injuries. This IoT-based digital sphygmomanometer is designed using the ESP32 microcontroller. A DC motor is used to apply pressure to the cuff, and a solenoid valve is used to release air from the cuff. The MPX5700AP sensor detects systolic and diastolic blood pressure, as well as BPM. The system also includes a motor driver to control the DC motor and solenoid, a Nextion LCD display to show blood pressure results, and a web server to display and store measurement data. The percentage of measurement error for systolic pressure ranges from the smallest error of 3% to the highest error of 25%. For diastolic pressure, the error ranges from 4% to 36%. As for BPM, the smallest error recorded is 13.6%, and the highest is 70.2%. This device helps patients monitor their systolic pressure, diastolic pressure, and BPM, with results saved and monitored through a database system.

The phenomenon that occurs in the load lifting system is the need for an efficient and reliable mechanism to move the crane hoist pulley vertically and horizontally. This study aims to design and test a crane hoist system that uses a DC motor and a stepper motor controlled by an L293D motor driver, and to develop an application based on MIT App Inventor to control the movement of the motor. The research method used is integrated hardware and software design, followed by testing the performance of the motor, driver, and the application developed. Testing was carried out under limited load conditions, to measure the motor speed, voltage, and current used at loads of 10 to 100 grams. The results of the study showed that the system can function well at varying speeds, and the motor is able to lift a maximum load of up to 100 grams with a speed that decreases according to the weight of the load. The MIT App Inventor application successfully controls the motor effectively via a WiFi connection with a maximum distance of 10 meters, and loads the operation of the crane vertically and horizontally. This study proves that the designed system is able to work optimally in lifting and moving loads, and the application developed provides easy and efficient control.

This research aims to design and simulate a DC motor speed control system using integral state feedback (KISF) control. This control is designed to maintain DC motor speed stability with high accuracy despite disturbances or load changes. The research stages include mathematical modeling of the DC motor, PID control design, integral state feedback control design, simulation implementation and simulation results analysis. The show that althought integral state feedback control has a rise time 273.501 ms, slightly slower than PID 197.604 ms, integral state feedback compensates with higher slew rate of change 6.540 V/ms compared to PID 4.344 V/ms. Integral state feedback offers greater flexibility through pole placement values with Ackerman’s formula J3 = [-12 -100 -600], indicating that this system has good capability in responding to input changes, thus maintaining motor speed stably and efficiently. This indicates that integral state feedback control is superior in system adaptation and handling complex dynamics.

In the era of maritime technology, Unmanned Surface Vehicles (USVs) are becoming the main vehicles on the water surface, controlled from land and capable of transmitting live data. USVs have a wide range of survey and exploration applications, relying on hydrographic knowledge for accurate mapping. USV development has adopted a double hull design, improving stability and wave resistance. Survey data transmission requires advanced technology, with Long Range (LoRa) technology being the solution for long distance data transmission with low power consumption. LoRa utilisation is expected to increase the efficiency of USVs in hydrographic surveys. The research and development (R&D) research method is used as the main approach in this research with the aim of creating and developing USVs that can increase efficiency in hydrographic surveys. The USV is equipped with an RPM sensor and flowmeter used to monitor the movement control of the USV in the waters. In addition, a depth detector is used to monitor the topography of the seabed. In order for this USV to run using a remote control that is controlled from land. The USV drive consists of a BLDC motor connected to the propeller and a servo motor connected to the ship's rudder. Furthermore, the data taken from the sensor is sent via LoRa to be delivered to the ground station. From the USV test results, it was found that the data transmission range with LoRa Ra-02 under Line of sight (LOS) conditions was 340 metres while under Non Light of sight (NLOS) conditions it was around 200 metres. The average speed travelled by USV is 0.616 km/hour in operational survey conditions and can be faster in non-operational survey conditions. The error value of the RPM sensor is obtained at 1.604% with a reading accuracy of 98.936%.