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The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

Indonesian Sign Language (BISINDO) serves as a primary communication medium for the deaf community; however, limited public understanding often creates barriers during daily interactions. This study aims to develop a real-time BISINDO word-level translation system using hand landmark extraction and temporal modeling with Long Short-Term Memory (LSTM). The system employs MediaPipe Hands to detect 21 hand landmarks per frame, which are then processed as sequential motion patterns to classify five BISINDO words: saya, terima kasih, maaf, nama, and kamu. A total of 250 gesture samples were recorded under controlled lighting conditions as the primary dataset. The processed sequences were used to train the LSTM model, which was subsequently integrated with an ESP32 microcontroller and a DFPlayer Mini module to produce direct audio output. Experimental results show that the model achieved an average accuracy of 86%, with precision and recall values ranging from 0.81 to 0.94. The confusion matrix analysis indicates that most gestures were correctly classified, although some errors occurred in gestures with similar initial motion trajectories. Integration testing demonstrated an average system latency of 3.8 seconds and an audio output success rate of 85%. These findings indicate that the proposed system is capable of translating BISINDO word-level gestures accurately, responsively, and consistently in real-time conditions. This study provides a strong foundation for the broader development of sign language translation systems, with potential enhancements in vocabulary expansion, multi-user datasets, and hardware optimization for deployment in real-world environments.

The problems in rice fields are complex and varied, depending on geographic location, rice variety, and growing season. Pests often cause serious economic losses. The Solar Sonic Repeller is an innovative portable pest control device designed to address pest problems by utilizing renewable energy, specifically solar energy. This product aims to offer an environmentally friendly and efficient solution. It works by emitting ultrasonic sound waves with a frequency of 30,000–40,000 Hz. The device's advantages lie in its portability and energy independence, thanks to the use of a charging module powered by an integrated photovoltaic (PV) panel with automatic battery charging during the day. The first test measured the output frequency using an oscilloscope to verify that the oscillator circuit produced waves at the specified frequency. The second test measured the device's effectiveness by examining the pest response to the device at various distances. This test was effective within a maximum radius of approximately 14 m from the center point, covering a rice field area of ​​250 m2.

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.

The manual employee attendance process at the Perjuk Village government level often results in inaccurate data, delayed recapitulation, and difficulties in real-time attendance monitoring. This study aims to develop an Internet of Things (IoT) and Radio Frequency Identification (RFID)-based village employee attendance system to simplify the administrative process and improve the efficiency of attendance recording. The development method used is the Research and Development (R&D) model with stages including needs analysis, system design, validation, field trials, and product revisions. The system was built using an ESP32 microcontroller, an RC522 RFID module, and a Wi-Fi connection to transmit attendance data to a web-based server. Testing was conducted using the black box method to ensure all system features run according to design. The results of the black box test show that all features run according to design. The system records attendance automatically with 100% accuracy, saves data to the server database, and displays reports in the form of tables, graphs, and statistical cards. The study concludes that this IoT and RFID-based attendance system is able to improve the accuracy, speed, and efficiency of recording compared to manual methods, and is in accordance with operational needs at the Perjuk Village Office.

Improving the accuracy of emission monitoring in the Continuous Emission Monitoring System (CEMS) is crucial to support compliance with environmental regulations, especially in gas and steam-based power plants (PLTGU). At PT Jawa Satu Power's PLTGU, the purging system on the CEMS sample probe is still performed manually and limited to scheduled preventive maintenance, potentially reducing emission data reliability due to particle contamination. This study aims to design and simulate an automatic purging system based on a Programmable Logic Controller (PLC), taking into account technical parameters such as timer, gas pressure, temperature, and sample flow rate. The system design was carried out through the modeling of automatic control logic using CX-Programmer software, with a protection approach based on real-time conditions and timing. The design results show that the automatic purging system can improve cleaning consistency, reduce the risk of contamination, and enhance the integrity of emission monitoring data. This study is expected to serve as a foundation for developing a more applicable and integrated automated purging system for CEMS in the future.

Digital transformation in government bureaucracy has become a strategic step to improve efficiency, accountability, and transparency, including in the management of regional legal products. In the Regional Secretariat of Tegal Regency, the process of submitting legal products is still done manually, which causes inefficiencies, delays, and a lack of document traceability. To address these issues, a web-based legal product submission application has been developed with document tracking features. This research uses the Waterfall system development method, and implements a FIFO (First In First Out) queuing system in the submission process, along with Role-Based Access Control (RBAC) for managing user access rights. The goal of this system is to create a faster, more transparent, and digitally documented application process. The implementation results show that the application is able to systematically and integratively manage the flow of submissions, corrections, verification, and the ratification of legal products. Features such as a Login page with CAPTCHA, analysis dashboards, tracking, and monthly reports enhance the monitoring and security functions of the system. This application can be an effective solution in supporting the digitization of regional legal bureaucracy, as well as providing ease and efficiency for regional officials in preparing and submitting drafts of legal products digitally.

The Message Queue Telementary Transport (MQTT) protocol is able to adjust the sending and receiving of messages to monitor in accordance with the user's preferences because the sending and receiving of messages is topic based on a specified topic, making it necessary to routinely monitor the condition of patients who have been diagnosed with heart problems from a distance. With the aim to perform a Quality of Service (QoS) analysis with throughput, delay, and packet loss parameters using Unshielded Twisted Pair internet transmission media (UTP) and Wireless, the goal of this research is to design and implement (MQTT) a heart rate monitoring device with an EKG module as a sensor and ESP32 as a microcontroller. On the Ubidots website, EKG signals are transmitted over the internet and shown in real time. QoS analysis is performed using the Wireshark application. Data was collected on two scenarios at intervals of 30 minutes, 1 hour, 2 hours, 5 hours, 8 hours, 12 hours, 18 hours, and 23 hours. The throughput, latency, and packet loss metrics used in this study's results cause different value variations; these are influenced by the weather, internet bandwidth, computer, and router specifications. According to testing, the tool is portable and has a 3000mAh battery, but it has the restriction that it can only be used with reliable internet and bandwidth.

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 food security program involving chili cultivation in Pentur Village is hindered by inefficiencies in water use and suboptimal plant growth, primarily due to traditional irrigation methods that fail to consistently maintain ideal soil moisture and temperature. This issue is exacerbated by unpredictable environmental shifts, such as fluctuating weather patterns, and a lack of precise irrigation control stemming from technological limitations. To address this, a system for monitoring and regulating chili plant irrigation using IoT technology was developed. This system employs humidity and temperature sensors connected to an IoT platform like Blynk, enabling real-time observation of plant and environmental conditions. Data on soil moisture, air temperature, and humidity are stored in a database, and irrigation is automated based on soil moisture levels. The goal is to enhance water efficiency, minimize risks associated with over or under-watering due to environmental variations, and improve both yield and quality of the chili crop. This IoT-based system aims to simplify chili plant management for Pentur Village farmers and significantly boost agricultural output.

Due to the busy activities outside the home, some people do not have time or forget to water their plants, so when they return home they find that the plants have died from drought. Therefore, to overcome this problem by conducting research using Internet of Things technology. The aim of this research is to design an automatic watering tool to overcome manual watering and support learning. This prototype uses a NodeMCU ESP8266 as the main controller, a soil moisture sensor is used to read soil moisture.  Soil moisture sensors are used to detect soil moisture. If the soil humidity is below the minimum limit, the watering process will be active and the watering process will be active if the NodeMCU ESP8266 receives commands from the smartphone.

CV. Apris Expressindo is a private company engaged in the construction and distributor of U-PVC frames. In its business process activities, CV. Apris Expressindo still does not utilize technology optimally, so that the transfer of information regarding offers, sales, purchases, product stock, suppliers, customers, and financial reports is still done manually. This causes inefficient business processes including: slow fulfillment of customer orders, product pricing errors between divisions, product marketing that is not optimal, financial reports that cannot be seen and controlled by company leaders. Therefore, it is necessary to implement Enterprise Resource Planning (ERP) which aims to overcome these problems. The methodology used in this study was carried out in several stages, namely, data collection: interviews, observation and literacy studies, business process analysis: activity diagrams and use case diagrams, implementation: installation, configuration and module customization, testing: blackbox and UAT (User Acception Test) . The results of this study indicate that the ERP software that has been selected and implemented, namely the Odoo application, can improve and simplify business process activities and can minimize any problems faced today. It is hoped that with this ERP system business operations can be more effective and efficient so that it is expected to provide more financial benefits for CV Apris Expressindo.

This research aims to design and build a system for stirring and monitoring temperature and humidity for ESP32-based compost fertilizer. This system uses an ESP32 microcontroller to control compost mixing and monitor temperature and humidity conditions in real- time. Data obtained from sensors will be sent to the server for monitoring via Blynk. The implementation of this system is expected to increase the efficiency of the composting process and produce high quality compost through optimal monitoring and mixing.

  Utilization of new renewable energy is a solution to meet the increasing electricity demand, one of which is solar power generation technology. Solar panels are a renewable power generator that is environmentally friendly. The relatively low and unstable output voltage of PV is affected by solar irradiation, which becomes a constraint. Therefore, by utilizing a boost converter, the solar panel system is able to work 25% more optimally compared to without using a boost converter. The performance of solar panels when using a boost converter is around 83.3% and without using it, the performance is only about 58.3%. The average output power when using the boost converter is 1,521 W, whereas without using the boost converter, the average output power is 1,172 W. This indicates that the output power is more stable when using the boost converter compared to not using it. This research focuses on a boost converter with PID control as a support, optimizer, and voltage stabilizer where the output power on the solar panel is expected to be more optimal and the output from the solar panel is more stable with more optimal results in various conditions. In this study, 12 solar panels of 125 WP with a capacity of 1.5 KW are used in series-parallel to obtain the required power. If the output from the solar panel is insufficient due to weather conditions, the voltage will be increased by the boost converter towards the inverter so that the voltage remains stable into the inverter with the boost converter. This boost converter uses PID control to keep the output voltage stable.  

Traditional doors usually consist of a housing or padlock and a flip key to open it. Usually found on office or mall doors, doors can be made more practical. The door will open automatically if there is physical energy (stimulus) that moves it. For example, when someone wants to enter the room, the door will automatically open. Doors like this are designed using automatic control using embedded system equipment. This automatic door system can be designed using automatic control combined with PIR sensors and servo motors. In terms of input equipment, a PIR (Passive Infrared Receiver) sensor is used which will detect humans approaching the door. This PIR sensor will send a signal to the Arduino process unit which contains a microcontroller chip. This microcontroller will send the processed data to the servo motor, so that it can open or close the door automatically.

Indoor air quality plays a vital role in public health, especially since people spend about 90% of their time indoors. Poor indoor air quality, often caused by chemical, physical, and biological pollutants, can severely impact health, comfort, and productivity. To tackle this issue, a robust air quality monitoring and control system was designed, featuring an ESP32 microcontroller paired with sensors such as the GP2Y1010AU0F dust sensor, MQ-7 carbon monoxide sensor, and MQ-2 smoke sensor, along with a fan to enhance air circulation. This system is capable of detecting air quality issues and taking corrective action. The ESP32 module, integrated with the Internet of Things (IoT) technology, enables real-time transmission of sensor data to a web server for continuous monitoring and prompt response. Researchers have made significant progress in creating an effective, system-based solution to improve and maintain indoor air quality

This paper presents the design and implementation of an automatic Virgin Coconut Oil (VCO) making device using an Arduino Uno microcontroller. Virgin Coconut Oil has gained popularity due to its health benefits and versatile uses in various industries. The traditional process of making VCO involves manual effort and precise timing, which can be tedious and inconsistent. The proposed automated system aims to streamline the VCO production process by integrating sensors, actuators, and a microcontroller to achieve precise control and monitoring of the process variables. The Arduino Uno microcontroller serves as the central unit for data acquisition, processing, and control, facilitating automation through programmed logic. Key components of the automated VCO maker include temperature sensors for monitoring heating stages, a motor for stirring, and relays for controlling heating elements. The system utilizes feedback loops to maintain optimal conditions during each phase of VCO production, ensuring reproducibility and quality. The design also emphasizes user-friendly operation, with an interface that provides real-time feedback on process parameters and allows manual intervention if necessary. Safety features are incorporated to prevent overheating and ensure operational reliability. Overall, the developed automatic VCO maker offers a practical solution to enhance the efficiency and consistency of VCO production, catering to both small-scale producers and commercial enterprises in the food and cosmetic industries

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.

Electricity theft is an activity that is detrimental to the state where PLN as the party that distributes electricity has unknowingly lost its main commodity without any reciprocity in the form of payment. To overcome electricity theft, Execution of Electricity Use (P2TL) is carried out. Implementation of Electric Power Use (P2TL) is an activity to control electricity users who do not comply with installation standards. P2TL activities include planning, inspection, technical and/or legal actions and settlements carried out by PLN on PLN installations and/or Electric Power User installations. P2TL activities carried out in the Koba area from October to December 2023 found 3 violations in the area. The kWh saved as a result of P2TL from October to December was 21,480 kWh. From the kWh savings obtained, the highest loss was in October of 0.47% and the loss obtained without P2TL kWh savings was 0.48%. So that the kWh savings obtained from P2TL can reduce Non-Technical Losses. The more P2TL violations are found, the higher the reduction in losses obtained by PT PLN (Persero) ULP Koba. 

At this moment, IoT technology was implemented in a broader area. The development of IoT technology can help human life become more manageable. IoT systems can help human activity through the natural time control system provided before. But there are some drawbacks when implementing the IoT system. One of them is the transmission process in the networking area. It’s happened because of weather, and other natural problems. Sometimes, IoT transmission can’t reach on time. It can make errors reading data on the user side. We proposed a transmission system, namely a Hybrid MP-QUIC transmission protocol, for helping in sending the data. Using this transmission protocol can reduce the response time between client and server.