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One of the goals of a building is to create a comfortable environment that does not affect the health and operations of its occupants, therefore a system needs to be created to ensure comfort in classrooms. To fulfill a comfortable situation, there is a standard that regulates comfort, especially thermal and visual comfort. Thermal comfort is regulated in SNI 03-6572-2001 and visual comfort is regulated in SNI 03-6575-2001. The aim of this research is to design a tool to automatically monitor temperature and lighting, determine greater accuracy, determine temperature and lighting comfort distances, and test Smart Comfort measurement results in accordance with the SNI-03-6571-2001 and SNI-03-6575-2001 conformity standards. This design uses ESP32 with IoT-based LDR and DHT11 sensors which can be seen on the web and application, determines the accuracy and range of Smart Comfort values for monitoring temperature and lighting and determines the suitability of measurement quantities in the SDN PINANG 3 classroom.

This study discusses the design and testing of a growing media moisture and water level monitoring system based on ESP32-MQTT. The system was developed to support real-time monitoring of growing media conditions and water availability through a monitoring dashboard. This research used an experimental method with a design and implementation approach by developing an ESP32 circuit connected to a capacitive soil moisture sensor and a water level sensor, then sending sensor data to the dashboard through the MQTT protocol and Node-RED. Testing was carried out using a plant pot as the moisture testing medium and a water container as the water level testing medium. The results showed that the growing media moisture sensor displayed 0% in dry and very dry soil conditions, 61% in moist soil, and 89% in very moist soil. The water level sensor displayed 0 cm, 2.4 cm, and 4 cm according to the testing conditions. These results indicate that ESP32-MQTT can be used as an initial prototype for monitoring growing media moisture and water level before being applied to a complete hydroponic or aquaponic system.

The computer laboratory is an essential facility in higher education that requires efficient management of usage and environmental conditions to support the teaching and learning process. However, laboratory management at the Kalimantan Business and Technology Institute is still carried out manually, including scheduling, room condition monitoring, and report creation, which is prone to errors and time-consuming. This study aims to develop an Internet of Things (IoT)-based laboratory monitoring system prototype to improve the effectiveness of computer laboratory management. The approach used is Research and Development (R&D) with a prototype development model, allowing for design adjustments based on user feedback iteratively. Data were collected through observations, interviews, and document studies related to laboratory conditions and analyzed to determine the main system features, such as temperature and humidity monitoring, scheduling, and report generation. The results of the study show that the developed prototype can structure the laboratory workflow, provide real-time monitoring, facilitate schedule management, and simplify report preparation. This prototype is expected to serve as a foundation for developing a more comprehensive application, improving data accuracy, time efficiency, and the quality of laboratory management.

The computer laboratory is an essential facility in higher education that requires efficient management of usage and environmental conditions to support the teaching and learning process. However, laboratory management at the Kalimantan Business and Technology Institute is still carried out manually, including scheduling, room condition monitoring, and report creation, which is prone to errors and time-consuming. This study aims to develop an Internet of Things (IoT)-based laboratory monitoring system prototype to improve the effectiveness of computer laboratory management. The approach used is Research and Development (R&D) with a prototype development model, allowing for design adjustments based on user feedback iteratively. Data were collected through observations, interviews, and document studies related to laboratory conditions and analyzed to determine the main system features, such as temperature and humidity monitoring, scheduling, and report generation. The results of the study show that the developed prototype can structure the laboratory workflow, provide real-time monitoring, facilitate schedule management, and simplify report preparation. This prototype is expected to serve as a foundation for developing a more comprehensive application, improving data accuracy, time efficiency, and the quality of laboratory management.

This study aims to develop a student learning progress monitoring system designed to assist teachers and parents in tracking students’ academic performance at SMP Negeri 2 Loura. The main issue identified in the school is that academic information is still distributed using manual procedures, which results in delays and limited transparency regarding students’ learning progress. To address this problem, the system was developed using the Model View Controller (MVC) architecture and the Waterfall approach to system development, which consists of several sequential phases such as analyzing requirements, designing the system, implementing the solution, conducting tests, and performing ongoing maintenance. The findings of this research show that the system that has been created is capable of presenting academic information in a complete and structured manner, including assignment scores, daily tests, and semester examinations. The system provides faster and easier access for teachers to input grades and for parents to monitor their children’s academic development in real time. Functional testing shows that all features operate correctly according to user needs, with no errors found during system operation.

Catfish farming is one of the fisheries areas with great potential in Indonesia. However, the problem of feed efficiency, use of probiotics, and air temperature control are still the main obstacles that affect the health and growth of fish. This study aims to design and implement an automatic system that can regulate the provision of feed and probiotics and control and control air temperature directly using the ESP32 microcontroller. This system has several important components, such as the ESP32 microcontroller as a control center, servo motors for feed and probiotic distribution, and DS18B20 temperature sensors to monitor air temperature. All components can be controlled and viewed through an IoT-based application with a Wi-Fi connection or applications such as Telegram. This trial aims to determine whether this system can provide feed and probiotics according to the specified time, and maintain air temperature in the optimal range (28°C–40°C) for catfish growth. In this way, the system is expected to increase efficiency in catfish farming automatically, reduce the need for human labor, and minimize errors in pond management.

Energy efficiency in water heaters is a crucial factor in ship operational environments due to limited electricity resources that rely on generators. This study aims to design and build an IoT-based water heater monitoring system with an innovative heat storage medium in the form of a mixture of silica sand and paraffin wax to improve thermal efficiency. Although previous studies have developed temperature monitoring and control systems in IoT-based water heaters, this study specifically fills this gap by analyzing the performance of adding silica sand to overcome the low thermal conductivity of paraffin wax. Using the Research and Development (R&D) method, this system was built with an ESP32 microcontroller as the control center, a DS18B20 temperature sensor for accurate measurements, and the Blynk and Google Sheets platforms for real-time monitoring and data recording. Performance testing was conducted by comparing the water heating rate between pure paraffin wax media and the mixed media. The results showed that the monitoring system functioned reliably, and the main finding proved that the addition of silica sand to paraffin wax significantly increased heating efficiency. This was clearly seen from the reduction in time required to raise the water temperature to 40°C, from 2.5 hours to only 1 hour in the second heating cycle. The results of this study indicate that the integration of silica sand and paraffin wax media with IoT technology can increase the efficiency of water heaters and provide an innovative solution for energy-efficient and environmentally friendly temperature control.

Suhu dan kelembaban merupakan parameter lingkungan yang harus dijaga pada ruang kubikel untuk memastikan peralatan distribusi listrik tetap bekerja secara optimal. Pada multi-kubikel, perbedaan fungsi dan beban menyebabkan karakteristik suhu dan kelembaban pada tiap ruang kubikel tidak sama, sehingga pemantauan secara manual menjadi kurang efektif dan efisien. Penelitian ini bertujuan untuk merancang dan membangun prototype sistem monitoring dan kontrol suhu-kelembaban pada multi-kubikel berbasis Internet of Things (IoT) yang terdiri dari tiga buah kubikel. Sistem ini menggunakan ESP8266 sebagai mikrokontroler utama dan sensor DHT20 sebagai sensor suhu dan kelembaban yang masing-masing dipasang pada kubikel dengan kondisi lingkungan berbeda. Sistem dilengkapi dengan aktuator kipas dan lampu, serta notifikasi real-time melalui LCD dan Telegram. Meskipun kontrol dan monitoring dilakukan secara terpisah pada tiap kubikel, notifikasi kondisi seluruh kubikel terintegrasi pada satu kanal Telegram yang sama. Pengujian kinerja sistem dengan memberikan variasi suhu dan kelembaban yang berbeda untuk tiap kubikel. Kubikel 1 diberi kondisi normal (suhu 35°C-40°C dan kelembaban 50%-70%), kubikel 2 diberi kondisi overheat (suhu di atas 40°C), sedangkan kubikel 3 diberi kondisi overhumidity (kelembaban > 70%). Hasil pengujian menunjukkan sistem mampu melakukan kontrol suhu dan kelembaban dalam ruang multi-kubikel serta mengirimkan notifikasi melalui Telegram dengan tingkat keberhasilan 100% dan rata-rata delay 5,6 detik.

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.

Renewable energy is non-fossil energy that can be renewed and managed sustainably, such as solar, wind, water, and biomass. To overcome dependence on weather conditions, this energy can be combined with alternative energy sources such as piezoelectric sensors, which can convert pressure into electrical energy. This study aims to design a prototype monitoring system for hybrid electric energy using solar panels, wind turbines, and piezoelectric elements as alternative energy sources on board ships. The use of Internet of Things (IoT) technology is key to monitoring and managing these energy sources in real-time and automatically through integrated sensors and software. This research uses the Research and Development (R&D) method by creating a prototype that combines solar panels, wind turbines, and piezoelectric components as energy sources and designing a monitoring system based on the Internet of Things (IoT) using the Kodular application. Several system components were tested through two types of testing: static and dynamic testing. The test results showed that the solar panel had the most stable performance with a voltage of approximately 16.50V and a current of 2.41A occurring between 13:00 and 16:00 WIB. The wind turbine was able to operate at low wind speeds and reached its highest voltage of 3.63V and current of 1.14A on the fifth day at 20:00 WIB with a wind speed of 1.1 knots. The piezoelectric system generated power according to the pressure and frequency of footstep impacts. The highest voltage recorded for a 70kg subject was 4.11V with a current of 0.19A. This hybrid system has the potential to be an environmentally friendly energy support solution on board ships.

Pemantauan suhu dan kelembaban secara real-time merupakan kebutuhan penting dalam berbagai bidang, seperti kesehatan, pertanian, industri, dan pengelolaan lingkungan, guna menjaga stabilitas kondisi ruangan dan mencegah kerusakan pada peralatan elektronik. Penelitian ini bertujuan untuk merancang dan membangun sistem monitoring suhu dan kelembaban berbasis mikrokontroler ESP32 dengan sensor DHT22. Sistem dirancang untuk menampilkan data secara langsung melalui layar OLED dan aplikasi Blynk sehingga memungkinkan pemantauan jarak jauh secara real-time. Penelitian ini menggunakan metode eksperimen dengan pengujian pada dua skenario, yaitu ruang tertutup dan area terbuka, dengan titik kendali kelembaban relatif (RH) sebesar 65%. Hasil pengujian menunjukkan bahwa sistem mampu bekerja secara efektif dalam kondisi ruang tertutup, di mana kelembaban meningkat dari 54,5% menjadi 65% RH dalam waktu 10 menit dan kemudian dapat dipertahankan stabil melalui mekanisme kendali otomatis. Namun, pada area terbuka, sistem tidak menunjukkan peningkatan kelembaban yang signifikan karena adanya sirkulasi udara bebas yang mempercepat dispersi uap air. Dengan demikian, dapat disimpulkan bahwa sistem monitoring berbasis ESP32 ini efektif digunakan pada ruang dengan kondisi lingkungan yang terkontrol, serta memiliki potensi untuk dikembangkan lebih lanjut pada aplikasi rumah pintar (smart home) dan sistem industri berbasis Internet of Things (IoT).

The coffee farming sector in Gunungmanik Village, Indonesia, plays a significant role in the local economy. However, the monitoring and management of coffee crops remain largely manual and conventional, making it difficult for farmers to respond quickly to environmental threats such as drought, pests, or sudden temperature shifts. This research presents the development of iotgm.id, a web-based monitoring system integrated with Internet of Things (IoT) devices designed to provide real-time environmental data for coffee plantations. The system measures key parameters including temperature, soil moisture, and motion detection (as a proxy for pest activity), and delivers this data via a user-friendly web interface. It also features digital farm record management, real-time alerts for abnormal conditions, and data visualization through interactive dashboards. Field testing with local farmers showed that the system improves decision-making, speeds up responses to environmental changes, and reduces the need for direct field visits. Unlike earlier systems that often required technical expertise or focused on single parameters, this system offers multi-parameter monitoring and is accessible to farmers without advanced digital literacy. The system bridges the gap between sophisticated agricultural technologies and practical field-level application. It contributes to the adoption of precision agriculture in rural areas, offering a scalable model for broader implementation in similar contexts

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.

In line with the rapid advancement of digital technology, the need for an efficient, integrated, and technology-based financial management system has become  critical, particularly for educational institutions such as STT-NF. The manual management of financial reports, especially cash flow statements used spreadsheets continues to pose significant challenges, including the risk of data entry errors, delayed reporting, and the lack of real-time visibility into the institution's financial condition. This study aims to develop a web application for cash flow monitoring system using the waterfall methodology to address these issues. The waterfall model was selected due to its systematic and structured approach. The system was developed using ReactJS for the frontend, NodeJS for the backend, and PostgreSQL as the database management system. To verify system functionality, testing was conducted using the black box testing method. The results of the testing indicate that all developed features of the cash flow monitoring system functioned according to the specified requirements and operated optimally. Therefore, the system is expected to provide tangible benefits in supporting the performance of the Finance Department at STT-NF as well as the foundation, by enhancing real-time financial visibility and delivering accurate information to facilitate faster & more informed decision-making.

Extreme climate change in Indonesia, caused by air pollution from the use of fossil energy, has encouraged the development of renewable energy technology, including Wind Power Plants (PLTB). This technology is increasingly important for providing clean energy, especially in the maritime industry. The aim of this applied scientific work is to provide a battery charging solution when the emergency battery charger charging system on commercial ships experiences problems. To make it easier to monitor the power produced by wind power plants and also battery capacity via a smartphone application in real time. The method used in this applied scientific research research is experimental. The results of calculating the average power during testing at night show an average power of 10.22 Watt/min and an average current of 0.78 A. So it can be concluded that battery charging takes 11.53 hours. Meanwhile, the results of calculating the average power during testing during the day show an average power of 13.41 Watt/min and an average current of 1.02 A. So it can be concluded that charging the battery lasts for 8.82 hours. From the two data obtained, it can be concluded that charging is optimal during the day because the efficient charging time is 8.82 hours.

A conveyor is a tool with a large rubber band arranged transversely between two pulleys at a constant speed as a transporter of solid material in this case coal with the provisions of the permitted amount. Damage to the conveyor tool has a major impact on the smooth running of a coal loading and unloading process, so a coal monitoring tool was designed using an ESP32 microcontroller-based data logger. The purpose of this study is to find out how to design a coal load monitoring tool based on a data logger using the Research and Development (R&D) method type ADDIE. Using the following types of testing: static and dynamic. The research results show that the load monitoring system based on a load cell and ESP32 microcontroller demonstrates high accuracy, with a reading deviation of less than 2% from the actual weight. The system is also considered effective, as it can detect loads, adjust the hatch door angle, and transmit data to Google Spreadsheet in real-time without disruptions. Its ability to adapt to varying loads indicates that the prototype operates stably, responsively, and in accordance with the design objectives.

Facial recognition, a branch of image processing, is widely used in attendance systems to improve efficiency and security. This study develops an employee attendance monitoring system that integrates facial recognition using the Eigenface algorithm in OpenCV. The system records each individual's facial data alongside a password, enabling automated attendance tracking. Testing results indicate that with a database of 10 facial entries, the system achieved 100% accuracy in recognizing individuals. However, as the database expanded beyond 10 entries, accuracy declined to 80%, influenced by factors such as lighting variations, differences in facial structures, and increased data volume. This study employed a Research and Development (R&D) methodology, with expert validation yielding a score of 3.4, categorizing the system as "Highly Valid." User testing with 11 participants resulted in an overall score of 36, classifying the system as "Very Good (Valid)." The findings highlight the potential of facial recognition in improving attendance management while minimizing fraudulent entries. Future research should focus on optimizing recognition accuracy in larger databases through refined preprocessing techniques, image quality adjustments, and deep learning models.

This study aims to design and develop a prototype of an Internet of Things (IoT)-based land watering monitoring system using the ESP8266 module and soil moisture sensor. This system is designed to help farmers manage watering automatically based on soil moisture conditions, so that they can save water and labor. The process at this time begins with a literature study, hardware and software design, to prototype testing on two soil conditions, namely dry and wet. Data from the sensor is sent in real-time to the IoT platform, if the soil is detected dry, the system automatically activates the water pump. The results of the test show that the sensor works accurately in distinguishing soil conditions, and the system is able to water automatically according to needs. Furthermore, this system can also be monitored and controlled remotely via the internet. The conclusion of this study shows that the use of IoT technology is very potential to increase efficiency and effectiveness in agricultural land management.

Traditional markets are characterized by fast-paced and diverse transactions, necessitating a reliable product monitoring system to enhance the efficiency of stock management and transactions. This study develops a monitoring system based on a loadcell sensor and a TCS230 color sensor to automatically classify product weight and type. The loadcell is used to measure product weight with high accuracy, while the TCS230 detects the color characteristics of products to distinguish between different types of commodities, such as various varieties of chili peppers. The development process includes sensor calibration, dataset collection, and the training and evaluation of a classification model. Experimental results show that the classification accuracy exceeds 90%, demonstrating the effectiveness of combining weight and color data for market product recognition.

Biogas is a renewable energy source with significant potential to reduce dependence on fossil fuels. However, conventional biodigester systems still face several challenges in monitoring methane gas production. Therefore, this research aims to design and develop a biogas digester prototype equipped with a stirrer and an Internet of Things (IoT)-based sensor to detect methane (CH4) gas levels. The research methodology involves designing a biodigester with an automatic stirrer and an MQ-2 sensor that can detect methane gas levels in real time. The data obtained is transmitted via ESP32 and displayed on the Blynk application. The research results show that the designed system can increase methane gas production and allow remote monitoring. The conclusion of this study is that the integration of IoT technology in the biodigester system can improve production efficiency and safety in biogas utilization.