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Penelitian ini mengembangkan sistem pemantauan berbasis Internet of Things (IoT) untuk mengoptimalkan kinerja Mini PC dan pemeliharaan real-time di CV Permata Gemilang Jaya. Metodologi waterfall diterapkan menggunakanNodeMCU sebagai mikrokontroler utama, dilengkapi dengan sensor DHT22, DS18B20, dan INA219 untuk memantau parameter suhu, CPU, dan memori. Arsitektur sistem mengintegrasikan kerangka kerja Laravel dengan database MySQL, menghasilkan aplikasi web responsif dengan kontrol akses berbasisperan untuk Admin Pusat, Admin Regional, dan Teknisi Cabang. Infrastrukturserver cloud dengan konektivitas GSM cadangan memfasilitasi pemantauanterpusat di wilayah Ciayumajakuning. Desain sistem menggunakan Unified Modeling Language (UML) dengan diagram kasus penggunaan dan diagram aktivitas yang komprehensif. Penerapan sistem pemberitahuan otomatisdengan mekanisme peringatan berbasis ambang batas memungkinkan deteksidini anomali perangkat. Antarmuka yang dioptimalkan untuk selulermeningkatkan aksesibilitas teknisi untuk operasi lapangan. Validasi sistemmenunjukkan strategi pemeliharaan preventif yang sukses dalam mengurangiwaktu henti perangkat dan mengoptimalkan efisiensi operasional infrastrukturteknologi informasi.

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.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring.

The knee is the largest joint in the human body. Like other joints, the knee consists of several structures, such as muscle cartilage, ligaments, tendons, and nerves. Almost all leg movements depend on the knee joint. Therefore, the Knee Brace or Health Knee Brace is a tool designed to provide stability support and reduce knee pain. The purpose of this study was to design and build an Arduino-based knee pain therapy tool and to test the safety and effectiveness of the tool in reducing knee pain. This tool is designed using Arduino Mega as a microcontroller, using a DS18b20 sensor that functions as a temperature reader on the Knee support which has a heater pad as a heat generator, a Vibration Motor as a vibration effect giver on the tool and a 2.4 TFT LCD Touch Screen as a display and a 12V adapter on this tool. According to the analysis of the tool made by the researcher, based on the results of the function and performance tests, the Arduino-based Knee Pain Therapy tool can function properly and safely.

Sinusitis is a health disorder commonly caused by factors such as air pollution, dust exposure, cold air, and smoking. With the rapid development of technology, there are now healing methods that do not rely on conventional medications, such as laser therapy. This research aims to develop a laser therapy clock equipped with sinusitis therapy using Low-Level Laser Therapy (LLLT). The system utilizes Arduino Nano as the main controller, an IR laser for the nose and hand, a DS18B20 temperature sensor to monitor the patient's temperature, and an OLED 0.96V display to show laser intensity and temperature values. This system aims to improve patient interaction with the device, providing a convenient and effective way to perform sinusitis therapy at home. The goal is to create a non-invasive, user-friendly solution for individuals suffering from sinusitis, with the potential to enhance treatment effectiveness, accessibility, and convenience, offering a promising alternative to traditional treatments.

Technological developments in the agricultural sector, especially in the hydroponic method, provide solutions for optimizing plant growth in urban environments. This research integrates ESP32 microcontroller technology with a DS18B20 temperature sensor and TDS sensor to monitor and control temperature and nutrient quality in a hydroponic system. In addition, the Sugeno fuzzy logic method is used for automatic water quality monitoring.

This research focuses on developing an IoT-based automatic irrigation control system for stevia plants to optimize plant growth and water usage efficiency. The system integrates ESP32 microcontroller with soil moisture sensors, DS18B20 temperature sensors, and DHT11 environmental sensors for comprehensive monitoring. Using Research and Development (R&D) methodology with an experimental approach, the system was designed and implemented to automatically control irrigation based on soil moisture levels. The results demonstrate that the system successfully maintains optimal soil moisture by activating the pump when moisture levels fall below 38% and deactivating it above 40%. Real-time monitoring through the Blynk platform enables remote observation and control of environmental parameters. The integration of multiple sensors with IoT technology provides an efficient solution for stevia plant irrigation management, offering potential applications in smart agriculture.

Freon is one of the refrigerants used in refrigeration systems. The refrigeration system has a very important role, namely to preserve food ingredients so that food can last longer. The use of freon is not only used in ships but is widely found in home appliances in refrigeration systems used in freezers, air conditioners, refrigerators, and dispensers. If more freon is used, the negative impact that arises is greater, namely the depletion of the ozone layer and global warming which can have a bad influence on health, the life of living things and the environment. The purpose of this researcher is to create a tool to reduce the negative impact of freon use, namely by using peltier as a cooling medium with environmentally friendly thermoelectric modules. This study uses trial and error methods. Where the trial process is carried out by turning on one of the working push buttons and observing the temperature value. Then it is processed by the control system, namely Arduino Mega which will later provide a PWM output signal to the IRF540 mosfet when the output temperature value is in line with the reference value and vice versa. The test of this tool was carried out by comparing measurements between the author's prototype tool and the standard measuring tool, namely the digital thermometer. Based on the test results, this device can produce a minimum temperature of 140C at 30-minute intervals without any media. The trial using 330ml bottled water can reach a temperature of 170C within 30 minutes in the cooler box. This tool is also equipped with an automatic monitoring system using a PWM signal in the form of a change in fan speed, which is 255 RPS maximum speed and when getting a PWM signal it changes to 50 RPS. The percentage of errors resulting from the comparison of standard measuring instruments and sensor values had the highest and lowest percentages of 2.37% and 0.84% in cold dispersion conditions without charge. Then the highest and lowest error percentages were 1.69% and 0.72% in the state of containing a load of 1 330ml mineral bottle. This ptototype uses data recording using Micro-SD as a data logger.

Sterilization is the eradication of materials, substances, or tools from various live microorganisms or their resting stages. Bacterial and fungal vegetative cells can be killed at a temperature of 60 °C within 5 to 10 minutes. A data logger is a tool used to monitor the temperature inside an autoclave. Previous research on "Autoclave Data Logger" aimed to assist in recording temperature activities within the autoclave. When the device is turned on, it automatically records the temperature inside the autoclave and stores the temperature data read on an SD card. After the sterilization process is completed, the SD card is retrieved for reading on a personal computer in Excel format or converted into a graph. Therefore, the author developed an IoT-based autoclave calibrator tool with data storage. This IoT-based autoclave calibrator tool with data storage utilizes the ESP32 microcontroller for programming and as a source in the IoT system. The ESP32 is used to control the input from the waterproof DS18b20 sensor, which functions to read or detect the temperature in the autoclave. The data read by the sensor will be displayed on the IoT platform, which is the Blynk IoT application, and after the results are displayed on the IoT platform, they will be stored on an SD card.      

Water is very important for all aspects of life on earth, agriculture is one of the fields that really need large amounts of water because of the use of water in the process of plant photosynthesis. Water that has good quality is if the water is not excessively polluted by harmful chemicals or minerals. One indicator that water is polluted is a change in temperature and pH (acidity) of the water. Temperatures that are too hot in the water will interfere with the growth of plants and other microorganisms. While the normal pH of water has a pH that ranges from 6.5 to 7.5. The quality of water and soil is very important in agriculture. The level of acidity (pH) and soil temperature are one of the things that affect plant fertility. Therefore, the quality of water and soil on agricultural land is one of the important things that needs special attention in its management. One solution so that water and soil quality can be monitored and managed efficiently is to utilize a Wireless Sensor Network based on the Internet of Things (IoT). The use of the ESP8266 Module as a WIFI module, is widely used by Internet of Things-based applications because the price is cheap so it reduces a lot of costs and has a fairly good speed of 80 MHz. This study aims to develop the concept of a Wireless Sensor Network by utilizing the ESP8266 module to monitor pH values using a pH Meter Analog Kit sensor and temperature from agricultural land using a DS18B20 Waterproof sensor and can be monitored at any time using a smartphone.

This research was carried out by comparing the DS18B20 sensor and the MLX 90614 sensor to detect the accuracy of detecting human body temperature which is used to detect Covid 19 symptoms. In this experiment, 10 trials were carried out with different human segments detected using the sensor. In the experiment, it was found that the MLX90614 sensor is more suitable to be used for development with an IoT-based system because it does not need to come into contact with the skin of the human body. The MLX90614 sensor will detect the temperature and change it to one Celsius unit then send it to the firebase database which will then be picked up by the android application which is held by the security officer so that the temperature can be known remotely. When the temperature is more than 38.5 Celsius it will turn on the buzzer sound which can be heard from a distance which indicates the temperature is above 38.5 Celsius and on android will also display a danger sign

Hydroponics are now increasingly in demand, should be checked regularly so that hydroponic plants thrive. Likewise, in Siliwangi Indah Hydroponics Semarang, which still uses manual methods, namely the absence of a device that detects nutrient water temperature and pH automatically and the absence of tools that can normalize nutrients automatically. Arduino Uno R3 can be used to detect temperature automatically with a temperature sensor DS18B20, and detect pH with a pH sensor. Then the sensor readings are sent to the farmer's cellphone with SMS Gateway. The sensor readings are also used to divert the flow of nutrients from the spare reservoir, so that the nutrients remain normal. So this tool can automatically measure the nutrient water temperature and pH and replace the main nutrients to the reserve nutrients. And the assessment obtained from experts on this tool gets a value of 3.6 and from the expert gets a value of 3.7. Hydroponic nutrition in this study is maintained normally and farmers always know the nutritional state. So that the hydroponic plants thrive and have maximum yields.