Publication Search

This research focuses on analyzing the performance of a vacuum pan automation sistem using solenoid valves at PT. Duta Sugar International as an effort to improve the efficiency and quality of refined sugar production. The vacuum pan is the main tool in the sugar crystallization process that functions to evaporate the sugar solution under low pressure. Problems faced in the manual sistem are temperature instability and high dependence on operators, which impact time inefficiency and decrease product quality. The purpose of this research is to design and analyze the implementation of an automatic control system based on a Distributed Control Sistem (DCS) with the integration of solenoid valve actuators to optimize temperature stability and cooking process efficiency. The research method was carried out using qualitative and quantitative approaches through direct observation, technical interviews with the automation team, and supporting literature studies. The results showed that the automatic system was able to maintain a stable cooking temperature in the range of 78°C–85°C, lower and more efficient than the manual system which fluctuates between 90°C–100°C. In addition, cooking time was reduced by 10–15 minutes per cycle, and the crystallization process became more uniform with more efficient energy consumption. The results showed that the implementation of DCS-based automatic control with solenoid valves significantly improved operational stability, productivity, and energy efficiency. Thus, this automation sistem proved to be an effective solution for optimizing vacuum pan performance in the modern sugar industry.

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.

The integration of Internet of Things (IoT) with cloud computing has revolutionized healthcare systems, offering scalable and real-time patient monitoring. However, optimizing response times and energy consumption remains crucial for efficient healthcare delivery. This research evaluates various algorithmic approaches for workload migration and resource management within IoT cloud-based healthcare systems. The performance of the implemented algorithm in this research, Hybrid Dynamic Programming and Long Short-Term Memory (Hybrid DP+LSTM), was analyzed against other six key algorithms, namely Gradient Optimization with Back Propagation to Input (GOBI), Deep Reinforcement Learning (DRL), improved GOBI (GOBI2), Predictive Offloading for Network Devices (POND), Mixed Integer Linear Programming (MILP), and Genetic Algorithm (GA) based on their average response time and energy consumption. Hybrid DP+LSTM achieves the lowest response time (82.91ms) with an energy consumption of 2,835,048 joules per container. The outcome of the analysis showed that Hybrid DP+LSTM have significant response times improvement, with percentage increases of 89.3%, 79.0%, 83.8%, 97.0%, 99.8%, and 99.94% against GOBI, GOBI2, DRL, POND, MILP, and GA, respectively. In terms of energy consumption, Hybrid DP+LSTM outperforms other approaches, with GOBI2 (3,664,337 joules) consuming 29.3% more energy, DRL (2,973,238 joules) consuming 4.9% more, GOBI (4,463,010 joules) consuming 57.4% more, POND (3,310,966 joules) consuming 16.8% more, MILP (3,005,498 joules) consuming 6.0% more, and the GA (3,959,935 joules) consuming 39.7% more. The result of ablation of the Hybrid DP+LSTM model achieves a 47.05% improvement over DP-only (156.57ms) and a 70.64% improvement over LSTM-only (282.41ms) in response time. On the energy efficiency side, Hybrid DP+LSTM shows 22.80% improvement over LSTM-only (3,671,51 joules), but 7.34% underperformance compared to DP-only (2,640,93). These research findings indicate that the Hybrid DP+LSTM technique provides the best trade-off between response time and energy efficiency. Future research should further explore hybrid approaches to optimize these metrics in IoT cloud-based healthcare systems.

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

This study investigates the impact of tail configuration variations on flight stability and battery energy efficiency in Unmanned Aerial Vehicles (UAVs). Three distinct tail types were tested: the conventional tail, the T-Tail, and the V-Tail. The objective was to compare how these tail designs affected the overall performance of UAVs, especially focusing on the balance between stability and energy efficiency. The experiments were conducted through a series of flight tests in a controlled outdoor environment, providing reliable and accurate data. During these flight tests, several performance metrics were recorded, including IMU-based angular deviations for pitch, roll, and yaw, energy consumption, flight time, voltage, and battery power. The data collected allowed for a thorough analysis of how the tail design influenced the flight characteristics of the UAVs. The results showed that the T-Tail configuration provided the highest flight stability, as indicated by the smallest angular deviations and minimal vibration during flight. This design’s enhanced stability made it the most reliable, especially for missions requiring precision control. In contrast, the V-Tail configuration proved to be the most energy-efficient, consuming only 22.80 Wh. Despite its low energy consumption, the V-Tail showed the lowest stability due to control coupling between the pitch and yaw axes, resulting in higher angular deviations and less precise control. The conventional tail, while not the best in terms of either stability or energy efficiency, struck a reasonable balance between the two. This configuration provided adequate stability while ensuring efficient battery usage, making it a suitable choice for general UAV applications. The findings of this study highlight the direct influence of tail design on UAV performance. There is a clear trade-off between flight stability and energy efficiency, with the conventional tail offering the best compromise.

The essential oil of lemongrass (Cymbopogon citratus) is a high-value commodity widely used in the food, pharmaceutical, and cosmetic industries due to its bioactive components such as citral. Optimizing its distillation process is necessary to achieve maximum yield with time and energy efficiency. This study aims to determine the hourly yield distribution of essential oil from Lombong-type lemongrass during steam distillation and to analyze its extraction kinetics to identify the optimal distillation duration. Distillation was conducted for four hours with yield recorded each hour, and the data were analyzed using pseudo-first-order and pseudo-second-order kinetic models. The results showed that the highest yield was obtained in the first hour (0.1882%), followed by a sharp decline, with no additional yield observed in the fourth hour. The pseudo-first-order model showed the best fit to the experimental data with a rate constant of k = 0,8012/hour. Meanwhile the pseudo-second-order model did not fit well. These findings indicate that the extraction process is dominated by external diffusion and the rapid release of surface volatile compounds. Therefore, it is recommended that distillation duration be limited to two hours to optimize energy and time efficiency.

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.

Global climate change has become a serious challenge that affects various aspects of life, including the field of architecture, especially in tropical climates. Increasing environmental temperatures and changing weather patterns have a significant impact on the thermal comfort and energy efficiency of buildings. This article aims to explain strategies for applying bioclimatic architectural principles as design solutions that are responsive to local climate conditions. Through systematic literature analysis, it was found that architectural design that considers climatic factors can increase comfort for occupants and reduce dependence on artificial lighting and lighting systems. This article also discusses various strategies for applying bioclimatic principles, such as the placement of the building's core orientation, window openings, balconies, transitional spaces, wall design, landscape relationships, passive shading, and heat insulation on the floor, where the application of these strategies can help create a more beautiful building. sustainable and energy efficient. Therefore, the application of bioclimatic architecture is very important to create buildings that can adapt well and efficiently in tropical areas.