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This research aims to design and develop a simple Dino-themed game based on a microcontroller, with the display using an I2C LCD. The game is inspired by the offline Dino game on Google Chrome, adapted to run on an Arduino Uno microcontroller. The research method used is Research and Development (R&D), consisting of stages such as needs analysis, system design, simulation using Wokwi, hardware assembly, programming, and testing. The system uses push buttons as input and a 16x2 I2C LCD as the output display. The testing results show that the system can respond quickly to user input and display character movement and score updates dynamically on the LCD screen. Although the graphical capability of the LCD is limited, the game runs well and successfully demonstrates the basic concepts of microcontroller programming as well as interactive input-output processing. Further development is recommended to enhance the graphical interface and add features such as sound effects and progressive difficulty levels.

Indramayu mango is a seasonal fruit that is highly favored due to its delicious taste and high nutritional content. However, high mango production is often not supported by adequate post-harvest facilities, particularly in terms of fruit ripeness classification. Currently, mango ripeness classification is still performed manually, which tends to be subjective and inconsistent. To address this issue, this study proposes a ripeness detection system for Indramayu mangoes by integrating the TGS2602 gas sensor and the YOLOv11 algorithm based on image processing. The TGS2602 sensor is used to detect ethylene gas emitted by ripe mangoes, while YOLOv11 is employed for visual image analysis of the fruit. This study aims to evaluate the system’s performance in classifying ripe and unripe mangoes, as well as analyze the integration between the gas sensor and the object detection model. The test results show that the TGS2602 sensor can detect increased ethylene gas concentration in ripe mangoes, while YOLOv11 demonstrates high accuracy in detecting mangoes based on visual images, with precision and recall close to 1.0. The system was also tested under various lighting conditions, including dark environments, and still performed well, although with a slight decrease in accuracy under low-light conditions.

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.

This study discusses the design and development of an automatic safety system for a wood cutting machine using Arduino Uno, a PIR (Passive Infrared) sensor, and a servo motor as the main components. The system is designed to automatically stop the movement of the wood cutting machine when human motion is detected around the cutting area, thereby minimizing the risk of work-related accidents. The research method includes hardware design, microcontroller programming, and system response testing using two types of test objects: the human body and a wooden block. The results show that the system operates according to the programmed logic. When the PIR sensor detects human motion, the servo motor stops and the red LED lights up as a danger indicator. In contrast, when no human motion is detected, the servo motor continues to move normally and the green LED remains on as a safe indicator. The system’s average response time is 0.6 seconds, indicating a fast and accurate performance. Therefore, the designed system is considered effective and can serve as a prototype of a simple safety tool to enhance operator safety in wood cutting machines.

The main problem with the water heating system on offshore platforms is the absence of water level monitoring and automatic overflow detection. This has the potential to cause hot water spills that endanger workplace safety and operational efficiency. This research designs and implements a water level monitoring system based on the Arduino Uno microcontroller with HC-SR04 ultrasonic sensors. The system is equipped with LED indicators, a buzzer alarm, and a 16x2 LCD to display water level status in real-time. Water levels are classified into three zones (low, medium, high), and overflow is detected if the water is within 3 cm of the sensor. Testing was conducted on a 5-liter simulation tank representing actual 500-liter tank conditions. Test results showed a reading accuracy of 96% and a quick system response to overflow conditions (<1 second). This system is economical, easy to develop, and highly applicable for offshore environments. In addition, this system can be integrated with IoT technology for remote monitoring.

This research presents the design and testing of an automatic color detection system using TCS3200 color sensor integrated with Arduino Uno microcontroller. The system was developed and tested using Wokwi virtual simulation platform before physical implementation. The TCS3200 sensor converts RGB light intensity reflected from objects into frequency signals, which are processed by Arduino Uno to classify colors into red, green, and blue categories. The system incorporates audio feedback using DFPlayer Mini module to provide sound notifications for detected colors. Testing results show that the system can accurately detect and classify primary colors with frequency-based thresholds: red (R<48 &R>37 & G<95 & G>85), blue (G<75 & G>65 & B<33 & B>23), and green (R<55 & R>40 & B<25 & B>5). The simulation validation demonstrates stable performance with consistent color recognition capabilities, making it suitable for industrial sorting applications and assistive technology for visually impaired individuals.

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.

Infusion Device Analyzer is a tool for testing the performance of an infusion pump and Syringe Pump. This tool measures flow and occlusion provided by the infusion pump and syringe pump. So a tool is needed to calibrate the infusion pump and syringe pump according to applicable standards so that swelling does not occur in the patient. The design of this calibration tool can also be used as student learning material so that students can understand and comprehend the working principles of the Infusion Device Analyzer. This tool is made using the Arduino Uno control system and there is an occlusion and flow measurement display along with room temperature and humidity which will be displayed on the Nextiton 4'3 Inch LCD. Accompanied by an optocoupler sensor as a liquid flow detector and an MPX5700AP sensor as a liquid pressure detector which is equipped with a DHT22 sensor as a room temperature and humidity meter. This calibrator tool is also equipped with a solenoid valve to regulate the entry of fluid to be measured between flow or occlusion measurements. The function test results show that the flowrate measurement of 10 is 12ml/h, 50 is 54ml/h, 100 is 105ml/h while the occlusion with a rate of 100 is 2.66 psi and the tolerance value for the parameters is appropriate. Therefore, the tool created is close to the desired plan and can be used as a suitable comparison of whether a Syringe Pump or Infusion Pump tool is suitable after repairs or during maintenance. This tool can also be used in learning for students to understand the parts of the working principle of this tool.

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.

Internet of Things (IoT)-based digital transformation has become a major catalyst in improving the efficiency of operational systems in various sectors, including the modern retail industry. One of the common logistics problems found in supermarket environments is the accumulation of unorganized shopping trolleys, which can hinder service flow and increase staff workload. This study presents a design of an IoT-based autonomous smart trolley system and automatic navigation to address these problems in a structured manner. The system design utilizes the integration of ESP32 and Arduino UNO microcontrollers, ultrasonic sensors for distance detection, line sensors for automatic path navigation, and Raspberry Pi modules for visual image processing in location tracking. The system is designed to be able to independently reposition the trolley to a predetermined parking station. Conceptual analysis shows that this system has significant potential in reducing operational costs, increasing labor efficiency, and strengthening customer service automation. Initial evaluation of technical and economic feasibility aspects strengthens the opportunity for widespread system implementation in the future. This design is the first step in developing a smart retail solution based on adaptive technology that is in line with the principles of Society 5.0. Furthermore, the development of this smart trolley system also considers user safety and comfort through additional features such as anti-collision sensors, an early warning system in the event of technical problems, and a manual control option as an alternative in emergency situations. The integration of Internet of Things-based technology also enables real-time monitoring and management systems through a web-based dashboard or mobile application, which can be accessed by supermarket management for operational analysis. Thus, this system not only addresses internal logistics needs but also contributes to improving the overall customer experience.

In the modern era, the need for sophisticated vehicle security systems is increasing along with the high rate of motor vehicle theft. This research designs and implements a fingerprint sensor-based vehicle security system using an Arduino Uno microcontroller. This system aims to improve security by utilizing biometric technology that can only be accessed by verified users. The fingerprint sensor is used to recognize the user's fingerprint, then activate the system through a relay instead of a conventional key. System testing shows a fast response time with an estimated rise time of about 0.5 seconds and settling time of about 2 seconds, without any misidentification (false positive or false negative). Thus, the system is proven to provide higher security, good authentication speed, and ease of use compared to conventional security systems. These results show that the implementation of biometric technology in vehicles has the potential to be widely applied.

Proses budidaya jamur tiram sangat tergantung dengan kestabilan pada kondisi lingkungan, terutama suhu ruangan dan kelembapan yang harus di perhatikan oleh para petani.  Hal ini menjadi permasalahan ketika proses pemantauan dan pengendalian lingkungan secara manual dilakukan, membutuhkan tenaga yang kuat dan waktu yang cukup besar. Penelitian ini bertujuan Mendesain rancangan sistem monitoring dan kendali suhu ruangan budidaya jamur tiram secara otomatis dan jarak jauh berbasis teknologi Internet of Things (IoT) untuk para petani. Dalam proses sistem ini penelitian ini memanfaatkan sensor suhu dan kelembapan DHT11 sebagai input, mikrokontroler Arduino Uno sebagai pemroses data, dan modul ESP8266 sebagai pengirim data nirkabel ke aplikasi Android berbasis Blynk.  Adapun metode dalam penelitia ini digunakan pengembangan yang digunakan adalah Software Development Life Cycle (SDLC) model waterfall, dan menganalisis kebutuhan, perancangan sistem, implementasi, pengujian, hingga pemeliharaan. Hasil pengujian menunjukkan bahwa sistem mampu membaca suhu dan mengaktifkan blower (kipas) secara otomatis ketika suhu melebihi ambang batas, serta menampilkan data suhu dan status kipas secara real-time melalui aplikasi Blynk. Dengan adanya sistem ini, pemantauan dan pengendalian lingkungan budidaya jamur dapat dilakukan lebih efisien dan fleksibel dan mendukung produktivitas budidaya secara optimal.

Technology is now increasingly advanced and developing rapidly. Almost every aspect of human life is now assisted by technology, especially computerized technology. This technology has penetrated almost all aspects of life and significantly increased efficiency in completing work. With the existence of computerized technology, many processes that were previously time-consuming and labor-intensive can now be done more quickly, easily, and efficiently. One example of the application of technology in everyday life is the design of a smart cupboard for storing shallots. This smart cupboard is designed to help shallot farmers and sellers store their agricultural products more efficiently. The working system of this tool is similar to the method of storing shallots in traditional huts, but with more sophisticated technology. This smart cupboard can regulate temperature and humidity automatically, which is very important to maintain the quality of shallots. The optimal temperature for storing shallots is between 25º - 30º C, with air humidity around 50% - 60%. If the temperature or humidity in the cupboard does not match the desired conditions, the system will automatically activate the lights and fans to return the temperature and humidity to the desired level. With this automated control system, shallots can be kept fresh for longer, reducing the damage that typically occurs to shallots due to unstable temperature or humidity. The advantage of this smart cabinet is that it can maintain the quality of shallots for a long time, even when stored in large quantities. This greatly assists farmers and traders in reducing losses due to perishable shallots and increasing the efficiency of shallot storage and distribution.  

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.

Oka Jamur Bali is one of the oyster mushroom cultivation farmers. Lack of efficiency in regulating temperature and humidity in mushroom barns is an important factor in the growth of mushroom fruiting bodies. This condition requires an innovative solution to regulate and monitor temperature and humidity in the barn area. This research aims to build a prototype using Arduino UNO, ESP32, DHT11, pump and Internet of Things (IoT) technology.  The monitoring system design uses Arduino UNO, NodeMCU ESP32, DHT11 and DC pump with 12V voltage. Arduino UNO functions as a control system to manage and control the temperature and humidity parameters of the mushroom barn environment with the DHT11 sensor used to accurately measure temperature and humidity. The combination of NodeMCU ESP32 and Arduino UNO aims for monitoring through the ThingSpeak platform which can be accessed with a smartphone connected to the internet network. Based on the results of the prototype of the automatic temperature and humidity control system, the system is able to measure the environmental conditions of the mushroom barn with humidity measurement results in the range of 79% - 82% and the average temperature during the test reached 29.35°C. The application of the system was able to reduce the temperature by 2.28% with an average temperature of 28.19°C and increase the relative humidity by 6.27% with an average humidity of 81.1% in the mushroom barn area. The results of income between the income generated by using the automatic temperature and humidity control system tool and the income of farmers without using the tool increased by Rp. 16,416.

Smart Door Lock is a development of a conventional manual home door lock or padlock. This study aims to create alternative technology at home by utilizing available lock technology. This study uses an Arduino Uno Microcontroller as the brain of the solenoid and as a power supply for the fingerprint scanner, and an esp 32 microcontroller as a tool for sending fingerprint data to firebase. The fingerprint scanner is run using the Arduino Ide to add fingerprints. Arduino programming is done using the Arduino IDE. The results of the study are described in the form of designing an automatic home door lock using a fingerprint scanner and Arduino as a solenoid control. The fingerprint data results will be visible in firebase

Socks are essential daily wear that require special care, including an effective drying process to prevent unpleasant odors and the growth of bacteria and fungi. Conventional drying methods often face challenges, especially in high-humidity environments or during unfavorable weather conditions. This study aims to design and develop a prototype sock dryer that is more efficient and hygienic. The prototype utilizes a combination of a heater, UV lamp, and humidity and temperature sensors to ensure optimal drying without damaging fabric fibers. A microcontroller-based control system using Arduino Uno is implemented to regulate device operation and monitor sock conditions during drying. Testing results indicate that the device effectively dries cotton socks in damp conditions faster than conventional methods. Additionally, the sterilization feature with a UV lamp helps reduce the risk of microbial growth. This innovation is expected to provide users with a practical, hygienic, and efficient way to dry socks without depending on weather conditions. Further development can be carried out to enhance drying capacity and energy efficiency.

This project aims to design and develop a prototype system based on gesture sensors to monitor visitors and smoke sensors to detect the presence of smoke in designated smoking rooms. The system is designed to enhance comfort, safety, and operational efficiency in multipurpose buildings. Utilizing the Arduino Uno microcontroller, the device is equipped with various components, such as a gesture sensor to detect visitor movements entering and exiting the building, enabling visitor monitoring for resource allocation. Meanwhile, the smoke sensor is designed to identify and monitor smoke concentration in the smoking room to prevent the spread of smoke to other areas.The device also includes additional features, such as an automatic exhaust fan and an LCD display for process monitoring. Test results show that the developed prototype has a high accuracy rate in detecting visitor gestures and can reliably and quickly detect the presence of smoke. This system provides an innovative solution to support smarter, safer, and more eco-friendly management of multipurpose buildings. This research is expected to serve as a foundation for further advancements in the application of sensor technology in public facilities.

The increasing unpredictability of climate change demands a system capable of automatically detecting rainfall and providing early warnings. This study aims to design and develop a rain detection system based on a water sensor and LED using an Arduino Uno microcontroller. The system operates by detecting water presence on the rain sensor and providing a visual indication through an LED. The research methodology follows a Research and Development (R&D) approach, including literature review, hardware and software design, implementation, and system testing. The test results indicate that the system can accurately detect rainfall and respond to weather changes in real-time. This system has the potential to be applied in various sectors, such as agriculture, transportation, and industry, to mitigate risks caused by sudden rain. Further development can integrate Internet of Things (IoT) technology for remote weather monitoring.

Neonatal asphyxia is a critical emergency condition in newborns characterized by the failure to initiate or maintain spontaneous and regular breathing, leading to hypoxemia, hypercapnia, and acidosis. One of the primary interventions to manage this condition is positive pressure ventilation using a resuscitation device such as a T-piece resuscitator or Neopuff. The Neopuff device has advantages over manual methods because it can provide stable and controlled Peak Inspiratory Pressure (PIP) and Positive End-Expiratory Pressure (PEEP), thereby reducing the risk of lung injury in newborns. The results show that the Arduino-based Neopuff device is capable of producing PIP pressures between 15–25 cmH₂O and PEEP pressures between 4–6 cmH₂O, which are within the recommended clinical standards for neonatal resuscitation. The pressure sensor successfully detected real-time changes, and pressure adjustment could be performed precisely. Therefore, this device can serve as a simple, affordable, and effective alternative for neonatal resuscitation, with potential for further development through an automatic control system to enhance accuracy and safety