Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Jurnal Ecotipe is a peer-reviewed journal published by the Department of Electrical Engineering, Faculty of Engineering, Bangka Belitung University (UBB). This journal accepts quality articles dedicated to all aspects of the latest extraordinary developments in the field of Engineering, especially in the field of Electrical Engineering. Jurnal Ecotipe has been Accredited by the Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia with the rank of Sinta 3. The Ecotipe journal is published 2 times a year (2 issues/year) in April and October.
Jurusan Teknik Elektro, Universitas Bangka Belitung
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Least Square-Based Modelling of 0.5 HP Single-Phase Induction Motor
A single-phase induction motor is a cost-effective device for converting electrical energy into mechanical energy, making it widely used by small and medium-sized enterprises (SMEs). Understanding motor characteristics and analyzing control system performance requires precise mathematical modelling. Nevertheless, it is difficult to derive models from physical laws, and frequently overlooks fundamental elements like usage duration and environmental conditions. This study proposes using the Least Squares method to model a 0.5 HP single-phase induction motor. With an MSE of 0.0307 and an RMSE of 0.1753, the results demonstrate that the estimated model closely resembles the real system, with only minor errors. Simulink simulations demonstrate consistent delay time and settling time values across different input variations in both open and closed-loop tests. In closed-loop conditions, rise time was nonlinear, with the slowest response occurring at 220 V and the fastest at 190 V. In open-loop conditions, rise time increased linearly with input reference. These results demonstrate that, without requiring in-depth knowledge of the physical system, the Least Squares method offers a productive and useful way to create precise mathematical models of single-phase induction motors.
Copyright (c) 2025 Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) http://creativecommons.org/licenses/by/4.0
Arduino-Based Capacitor Bank Automation for Power Factor Optimization
Electrical energy efficiency in PLN customers in the R1 category is a crucial issue due to the low value of the power factor (cos φ), which is caused by the dominance of the use of inductive equipment. This condition not only causes significant energy waste but also puts a strain on the power grid, where the urgency is amplified by various economic factors. This resaerch designed an automatic capacitor bank system to dynamically correct the power factor. By integrating the Arduino Nano microcontroller and the PZEM-004T sensor, the system monitors electrical parameters such as voltage, current, and cos φ in real-time. Based on this data, the system autonomously activates the relay to connect capacitors with the most optimal capacitance value to compensate for reactive power precisely. Its main innovation is an adaptive automation mechanism that is able to respond to load fluctuations. The implementation aims to increase the cost value φ close to 1.0, so that it has great potential to reduce power losses, reduce electricity bills, and improve the overall efficiency of the electrical system.
Integration of AI Models and Extreme Programming for Retail Price Prediction and Inventory Optimization
Food prices in modern retail are highly volatile and complex inventory management is often an obstacle to maintaining operational efficiency. The research developed Smart Retail AI, an artificial intelligence-based application that integrates Long Short-Term Memory (LSTM) for price prediction and Extreme Gradient Boosting (XGBoost) for stock optimization. The software development method uses the Agile Extreme Programming (XP) approach, which emphasizes rapid iteration, user engagement, and continuous testing. The test results showed that all application features worked according to the specifications through Black Box Testing, while the usability test using the System Usability Scale (SUS) resulted in an average score of 87 (Excellent category). These findings confirm that the app has high reliability and an excellent level of ease of use. The novelty of the research lies in the direct integration of AI-based predictive models into real operational retail applications with the XP cycle, thus bridging the gap between algorithmic research and practical application. Overall, Smart Retail AI contributes to improving decision-making efficiency, operational responsiveness, and business sustainability in the modern retail ecosystem.
Adaptive PID–PD Hybrid Control for Precise Motion of ROVs in Dynamic Environments
This study aims to develop and evaluate an Adaptive PID–PD Hybrid Control System to enhance the position and rotation control of a Remotely Operated Vehicle (ROV) in challenging sea conditions. In this study, two main stages were conducted. First, a dynamic model of the ROV was developed, encompassing translation for movement in three-dimensional space (x, y, z) and rotation for changes in orientation (roll, pitch, yaw). Second, the adaptive PID–PD hybrid controllers were implemented and evaluated on the ROV model to ensure stability and precision in motion control. Simulation results demonstrate that the proposed controller effectively maintains position with surge overshoot of 23.3%, sway of 1.67%, and heave of 47.17%. The settling time ranges from 41.53 to 107 seconds, indicating areas for further tuning. In terms of velocity response, surge velocity shows a high overshoot of 106.26%, while sway and heave velocities present smaller overshoots but require longer stabilization times. The integration of PID and PD in a hybrid adaptive framework yields improved inner-loop response and overall robustness. These findings highlight the potential of the adaptive hybrid controller to enhance stability, responsiveness, and operational effectiveness of ROVs in dynamic marine conditions.
A Comparative Study of Traditional PID Tuning Techniques and AI-Based Algorithmic Approaches Utilizing the Python Control Library
This study aims to compare PID parameter settings with conventional tuning methods and tune methods using AI (artificial intelligence) algorithms. This study was conducted by means of simulation using a computer program created in Python and utilizing AI libraries to solve the problem of determining PID (proportional-integral-derivative) parameters. Two AI algorithms used in this study, namely the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods, were compared with the conventional Ziegler-Nichols method. The study was conducted by applying the PID parameters obtained to a certain transfer function and then comparing them on several related aspects. The results of the study showed that the solution obtained using the AI method requires a longer execution time, more than 2 seconds for PSO and more than 3 seconds for GA, while ZN requires less than 1 second. However, the AI method can provide better solutions, as can be seen from the magnitude of the ITAE that occurs, where GA and PSO provide ITAE less than 1 while ZN is more than 22.
Optimization of Spot Welding Performance Through Microcontroller- Solenoid Drive and Ultrasonic Sensing
This research discusses the design and testing of an Arduino microcontroller-based spot welder control system with solenoid drive and ultrasonic sensor as the main input. The system is designed to improve efficiency, precision, and consistency of welding results by automating the electrode clamping process as well as voltage regulation according to material specifications. The combination of a relay and voltage regulator module allows the current to be optimally adjusted based on the thickness of the work plate, thereby reducing welding defects. Tests show that the system is capable of detecting objects within 10 cm, and a welding time setting of 3 seconds proves sufficient to produce an optimal weld point. On plates with a thickness of 1.44 mm, the best results were achieved at voltages of 4V and 6V; for thicknesses of 1.8 mm and 2.2 mm, the optimal voltage was 8V. The pressure from the solenoid proved to be sufficient in joining the materials well. These results show that the microcontroller-based welding system is effective in adaptively managing the welding time and voltage, and provides consistent and robust results. These findings support the potential application of the system in smarter and more automated production processes in accordance with industry 4.0 principles.
A New 12-Phase Toroidal Transformer Design to Improve Efficiency and Power Quality in Electric Vehicle Fast Charging Systems
Transformers are essential components in electric vehicle (EV) fast charging systems, particularly in ensuring high efficiency and maintaining power quality. This study introduces a new design and implementation of a 12-phase toroidal transformer integrated into a 50 kW fast charging system. The main contribution of this research lies in improving energy efficiency, thermal stability, and harmonic suppression, which are critical challenges in conventional transformer configurations. The proposed transformer was modeled and simulated using MATLAB/Simulink, followed by prototype fabrication and experimental validation. Simulation and test results demonstrated that the 12-phase toroidal transformer achieved an efficiency of 98.3%, representing a 2.2% improvement over a conventional 6-phase configuration. Furthermore, steady-state coil temperature decreased by 10°C, while DC voltage ripple was reduced from 6.7% to 3.2%. Harmonic performance also improved significantly, with Total Harmonic Distortion (THD) dropping from 7.8% to 4.5% at the AC side and from 4.2% to 2.1% after rectification. In terms of charging performance, the system successfully shortened the charging time for an 80% state of charge (SoC) battery from 32 minutes to 27 minutes, a reduction of 15.6%. These findings confirm that the 12-phase toroidal transformer provides a technically reliable and novel solution for next-generation EV fast charging infrastructure, delivering both high efficiency and improved power quality.
Solar Power Plant of Apartment Kertapati – A Design Study to Reduce Carbon Emission
Energy demand in residential and housing areas in Indonesia is still predominantly reliant on fossil fuels. This dependency grows, triggering various environmental issues such as air pollution and global warming. Furthermore, energy costs in these areas are relatively high, partly due to increasing tariffs from PLN (Indonesia’s state electricity company). One residential area in Palembang City with the potential for developing a Solar Power Plant (Solar PV System) is the Kertapati Rental Apartment Complex (Apartment Kertapati), located in Karya Jaya Sub-district, Kertapati District, Palembang City, South Sumatra. This area spans approximately 7 hectares and consists of a total of 300 units. Energy demand in this area is significant, particularly to support public and social facilities such as lighting, cooling systems, and various other needs. This study utilises PVsyst software, which is designed for the planning, simulation, and analysis of solar power systems. With the identified energy needs and favourable environmental conditions, this project has significant potential to deliver both economic and environmental benefits. However, this study focuses exclusively on on-grid systems for analysis and data processing.
Development of a Library Information System for Data Processing at SMK N 1 Pangkalpinang
SMK N 1 Pangkalpinang is a vocational school in Pangkalpinang City with a library that plays a vital role in supporting the learning process. However, its current data processing system is still manual, relying on Microsoft Office and lacking integration. This creates issues such as difficulties in book searches, recording errors in borrowings and returns, and limited report generation. This study aims to develop an effective and efficient desktop-based library information system. Data collection was conducted through direct observation and interviews to gather system requirements. The system was designed using an object-oriented approach with Unified Modeling Language (UML) tools, including use case, class, sequence, and activity diagrams to visualize system processes and logic. The resulting application includes features such as member and book data management, automated borrowing and return transactions, and computerized report generation. It improves administrative accuracy and speed, enhances data access, and supports real-time, systematic reporting. The use of UML and object-oriented methods ensures the system is flexible and scalable for future development. This innovation significantly improves the quality of library services at SMK N 1 Pangkalpinang.
Comparative Study of Sentiment Analysis for Interpreting the Customer Interest in Women Fashion Clothes
Public sentiment is widely recognized as a key factor influencing fluctuations in stock prices, product sales, and emerging trends. Since the user interest analysis played an essential role in representing the trend of the market and it is also extremely useful for generating the strategy and decision of trading, analyzing the public sentiment is quite important. In the contemporary era, virtual space has been perpetually evolving and used in plenteous applications including analyzing customer interest. This research work aimed to conduct comparative study in analyzing customer interest about women fashion clothes using sentiment analysis method-based machine learning approach. The proposed study was initiated by conducting data acquisition process. It was then continued with labelling and predicting the user sentiment by comparing eleven machine learning approaches. According to comparison result, Naïve Bayes successfully obtained the best performance with accuracy of 94%, precision of 87%, recall of 82%, f1-score of 84%. It can be inferred that Naïve Bayes was viable approach for predicting the user sentiment.
Design and Simulations of 2x1 Rectangular Microstrip Array Antenna Using Inset and U-Slot Method at 3.5 GHz for 5G Communication System
This paper presents the design and realization of a 2×1 rectangular microstrip array antenna operating at 3.5 GHz for 5G communication systems. The design incorporates inset feed and U-slot techniques to improve antenna performance in terms of return loss, gain, and bandwidth. AWR Microwave Office 2009 was used for simulation, and iterative optimization was conducted on parameters such as feed position and slot dimensions. The final prototype achieves a return loss of –36.75 dB, a gain of 9.246 dB, a VSWR of 1.115, and a bandwidth of 169 MHz. These results demonstrate the effectiveness of combining array configuration, inset feed, and U-slot techniques for enhanced antenna characteristics.
Development of a Mental Health Consultation Website Using the Waterfall Method (Case Study of Biro Psikologi Putra Tunggal)
Mental health is an important issue that requires improved accessibility and efficiency in psychological services. Klinik Biro Psikologi Putra Tunggal, which serves various communities in Banyumas Regency, has a website as an information platform but does not yet support online consultation features. Therefore, this study aims to develop a web-based mental health consultation system to enhance the accessibility and effectiveness of psychological services. The system development follows the Waterfall method, consisting of analysis, design, implementation, testing, and maintenance stages, ensuring each phase is evaluated before progressing. The developed website includes user, service, and article management features for administrators; online and offline consultations by psychologists; as well as service booking and communication via chat rooms for patients. The system was tested using Blackbox Testing with descriptive analysis, yielding a feasibility score of 100%, Thus, the system is considered to be functioning properly and ready for deployment. The System Usability Scale (SUS) test showed that the new website scored 77.16, higher than the previous version, which only reached 69.5. With more comprehensive features, this website is deemed feasible and effective in improving the accessibility and efficiency of mental health services.
Prototype of Seaweed Dryer Operating in Manual and Automatic Mode Using Wi Fi Based Microcontroller
This study discusses the development of a seaweed dryer prototype that can operate automatically or manually using a Wi-Fi based Nodemcu ESP826 microcontroller and Telegram application. The operation of the tool can choose automatic mode, where the system regulates the temperature independently, or manual mode via telegram to control the drying parameters directly. The drying process can be carried out by operating an incandescent lamp as a heat generator and a fan to generate air flow in the seaweed drying area. Testing the tool with automatic mode is by installing a rainwater sensor that will give a signal to the microcontroller to order the motor to rotate to open or close the roof and turn on the lights and fan, while in manual mode the roof opening and closing operation is carried out by changing the use of automatic mode to manual on the telegram command. The test results are in the form of voltage measurements on each component and this tool can operate in both modes. When the drying process takes place the incandescent lamp and fan will be active or ON, and when the water sensor receives rainwater the drive motor will immediately be active to close the roof, and all systems will automatically be OFF. This prototype is feasible to be implemented into a real tool to help seaweed farmers in the seaweed drying process to be more efficient, easier to control, and can improve the quality of the final seaweed product.
Design and Contruction of a Website for Garbage Sales in Sirau Village Using the Extreme Programming Method (Case Study of KSM Kudu Bisa)
Waste management remains a critical issue in Indonesia, including in Banyumas Regency, where increasing volumes are driven by population growth, urbanization, and low public awareness in waste sorting. In Sirau Village, the KSM KuduBisa waste management group faces various operational challenges, including the absence of real-time waste data, manual transaction records, and high operational costs. This study aims to design and develop a digital waste sales platform using the Extreme Programming (XP) method, chosen for its adaptability and emphasis on continuous testing. The system was built using the full-stack Next.js framework, allowing integrated front-end and back-end development, and was evaluated through Blackbox Testing and the User Experience Questionnaire (UEQ). The results showed a functional success rate of 98.96% and excellent usability scores across all UEQ dimensions. The novelty of this research lies in the integration of digital waste transaction features with educational content within a role-based, modern web architecture—an approach that not only enhances operational efficiency but also promotes public awareness and engagement in sustainable waste practices.
A New MPPT Scheme Based on Komodo Mlipir Algorithm for Stand-Alone Solar PV System
The efficiency of PV modules remains relatively low, ranging from 15% to 35%, depending on the type of silicon technology used, including crystalline, polycrystalline, and thin-film. Then, the energy extraction efficiency from Solar Power Generation could be a lot higher (below 70%), especially in Solar Power Generation systems that still need to implement the Maximum Power Point Tracking (MPPT) algorithm. The MPPT algorithm is implemented in power electronic devices, such as boost converters, to optimise the power output of solar modules under various operating conditions, particularly during partial shading conditions. Various MPPT algorithms have been developed, each with its strengths and weaknesses. To enhance the efficiency of Solar Power Generation, this research will use a more effective state-of-the-art algorithm, namely the "Komodo Mlipir Algorithm" (KMA). KMA exhibits low system exploitation characteristics, utilising high exploration strategies, which align with the hunting behaviour of the Komodo dragon. This algorithm is expected to increase Solar Power Generation efficiency to above 90%.
Statistical Analysis of Protection Current Transformer Performance Based on Error Ratio and Knee Voltage on 20 kV Feeder at Bangka Transmission and Substation Service Unit
Current Transformers (CTs) are essential components in power system protection, ensuring accurate current measurement for relay operations.. This study evaluates the accuracy of protection CTs used in 20kV feeders at the Bangka Transmission and Substation Service Unit. Measurements were conducted on CTs with 5 and 7 years of usage to analyze ratio error and knee voltage compliance with IEC 61869-2 standards. The results indicate that all CTs meet the standard, with ratio errors below 1% and knee voltages exceeding 60V. Normality tests confirmed that the data are normally distributed, allowing statistical analysis using t-tests. The t-test results showed no significant difference in ratio error and knee voltage between CTs used for 5 and 7 years. This study concludes that aging over this period does not significantly affect CT accuracy, ensuring continued reliability in power system protection.
Effect of Tilt Angle on Solar Cell Efficiency and Electrical Energy of Nanofluid Filled Photovoltaic-Termal (PV/T) Systems
This study aims to analyze the effect of nanofluid concentration and panel tilt angle variation on photovoltaic-thermal (PV/T) system efficiency using numerical simulation with the Finite Element Method (FEM). The results showed that the optimal nanofluid concentration of 20% resulted in an even distribution of fluid flow, while increasing the concentration to 20% at an inclination angle of π/6 decreased the PV cell temperature, increased the photovoltaic efficiency to 12.04%, and the best electrical power of 36.71 W. The highest thermal efficiency of 69.5% was achieved at a concentration of 20% with an inclination angle of π/6, while the highest total efficiency of 81.7% was achieved at an inclination angle of π/3. The optimal combination of nanofluid concentration and tilt angle was shown to significantly improve the energy efficiency of the PV/T system, making an important contribution to the development of more efficient renewable energy technologies.
Analysis of Characteristics of Three Phase Transformer Using MATLAB
Three-phase transformers are integral components of modern electrical power systems, serving as the backbone of energy transmission and distribution networks. Their primary purpose is to step up or step-down voltage levels efficiently, enabling the transfer of electrical power over long distances with minimal losses. Due to their widespread use in industrial, commercial, and residential applications, understanding the operational characteristics of three-phase transformers is crucial for improving energy efficiency, ensuring reliability, and optimizing performance. The analysis of transformer characteristics, such as efficiency, voltage regulation, power losses, and behavior under varying load conditions. This research aims to analyze the characteristics of three-phase transformers using MATLAB. The results of the analysis obtained in the study of the characteristics of 3-phase transformers produce an active power (P) of 6183.42 W, a reactive power (Q) of 3832.14 VAR, an apparent power (S) of 7274.61 VA and a transformer efficiency of 97.75% with a time of 0.02 s and produces losses in copper of 81.65 W which forms electromagnetic field radiation where the radiation pattern of the electric field (E field) and the magnetic field (H field) is in the form of a polar graph.
Review on Innovative DC-DC Converter Design for High Efficiency and High Voltage Gain Applications
This paper reviewed the advancements in DC-DC converter technologies, emphasizing their role in addressing the demands of high efficiency and high voltage gain in renewable energy systems, electric vehicles (EVs), and distributed energy networks. Advanced topologies, including hybrid, quadratic, triple-boost, coupled inductor, and voltage multiplier designs, were evaluated for their ability to overcome the limitations of traditional converters. Key findings highlighted significant improvements in energy efficiency, exceeding 95%, and a substantial reduction in voltage ripple. Performance metrics such as scalability, thermal management, and component stress were analized, demonstrating the suitability of these designs for diverse applications. Comparative analyses illustrate the superiority of innovative designs in meeting the energy needs of emerging technologies. Applications in renewable energy, EV infrastructure, and distributed networks underscore the transformative potential of these converters in optimizing power delivery and enhancing system reliability. This review bridged the gap between theoretical advancements and practical implementations, showcasing the pivotal contribution of DC-DC converter to modern energy systems.
User Capacity Optimization Using The Mobility Load Balancing Algorithm For Downlink Data Long Term Evolution
The increasing number of users in a Long Term Evolution (LTE) network often decreases network performance. A cell that has high traffic experiences a decline in network performance due to unavailable resources for certain users, while in cells with low traffic, the use of resources in these cells is inefficient. The mobility load balancing (MLB) algorithm balances the intercellular loads in an LTE network and improves the performance by distributing part of the load in a high traffic cell to neighboring cells that have low loads. An activated MLB will detect the network load and calculate the available resource for each cell to determine which cells are overloaded. The MLB will consider the candidate cell where the load could be distributed. MLB simulation results show that the application of MLB has succeeded in reducing the percentage of unsatisfied users by 9.4% and increasing throughput system to 5.617 Mbps.
Improving the Effectiveness of Help Desk Service Management in the Self-Service System at the UIN Sunan Ampel Surabaya Academic Library
The increasing reliance on self-service systems in academic libraries necessitates robust service desk man-agement to ensure user satisfaction and operational efficiency. At the UIN Sunan Ampel Library, self-service systems provide convenient access to various services, but their performance remains underexplored. Evaluat-ing the library's service desk management using the ITIL V4 framework reveals critical insights into its effec-tiveness and areas for improvement. The framework’s Service Desk Practice Success Factors (PSF)—Acknowledge, Classify, Own, and Act—are used to assess how well self-service systems align with ITIL best practices. This research adopts a qualitative descriptive methodology, utilizing interviews and data analysis to evaluate service desk processes. The findings indicate significant benefits in accessibility and user empower-ment through self-service features. However, challenges persist, including manual acknowledgment workflows, insufficient SLA implementation, and limited real-time monitoring capabilities. These issues hinder optimal service delivery and responsiveness. To address these gaps, the study recommends integrating automation for acknowledgment tasks, developing measurable SLA policies, and implementing comprehensive training for library staff. Additionally, real-time tracking tools should be incorporated to enhance system efficiency and user experience. Despite these challenges, the study underscores the potential of ITIL V4 to improve library service desk management, ultimately fostering better user satisfaction and operational excellence.
Implementation of Fuzzy Logic for Early Warning System for Flood Disaster in Cilacap District
Indonesia's tropical climate and high rainfall frequently lead to unnoticed river overflows, causing significant health and economic losses. A Flood Early Warning System (EWS) using LoRa communication and an Arduino Mega2560 microcontroller was developed, incorporating ultrasonic, DHT11, rain gauge, and anemometer sensors to measure water level, temperature, humidity, rainfall, and wind speed. Unlike previous systems, it applies fuzzy logic for improved accuracy by considering rainfall and wind speed. Sensor errors ranged from 2.14% to 3.19%, with data transmission to ThingSpeak taking 11 seconds (99.94% accuracy) and to a website averaging 15.03 seconds. Fuzzy logic enhanced the system's warning accuracy.
PI Control Application for Low Speed Stepper Motor in Medical Infusion Pump for Flow Rate Stability
An infusion pump is an intravenous injection machine for administering high-alert type drugs. Failure to administer this type of drug can result in the patient's death. One of the causes of failure is disturbances in the infusion fluid flow rate, which is influenced by the performance of the stepper motor. This research proposes a PI control design for controlling flow rate stability in infusion pump machines. PI is applied by simulating Simulink using the Ziegler Nicholes type 1 tuning method and creating a 1st-order transfer function using the Cian Cone method. The system is also applied directly to the hardware and tested using standard medical calibration tools. The simulation results show that the PI control can reach the set point and maintain stability with a rise time of 19.49 seconds and a settling time of 32.39 seconds. In actual testing of the infusion pump machine with PI control, the average level of accuracy of the flow rate reached 98%, and the stability reached below 0.3 ml/h. This proves that the infusion pump that has been successfully created can be used to administer high-alert drugs precisely according to the dosage and can be used for a long time with constant delivery quality.
Design of PID Controller using LQR-Based Parameter Selection for DC Motor Position Control
DC motors are widely applied in various fields due to their simple design, ease of control, and capability to generate high torque at low speeds. Position control of DC motors is crucial to ensure the performance and accuracy of the motorized electro-mechanical systems. The most common conventional control utilized in DC motors is the Proportional Integral Derivative (PID) controller. However, selecting the proper parameters for that controller is challenging. In this paper, the Linear Quadratic Regulator (LQR) approach is used to determine PID controller parameters for DC motors. The LQR approach, based on optimal control theory, offers a systematic alternative to traditional trial-and-error methods for tuning PID controllers. The proposed method improves the performance and efficiency of DC motors by optimizing the PID parameters, ensuring precise control and energy utilization.
Development and Design A Queue Service System Banyumudal Health Center Using the Waterfall Method
Puskesmas Banyumudal is a health care facility in Pemalang Regency, located at KM 1, Banyumudal, Jalan Raya Moga-Karangsari, Moga District, Central Java. This health center aims to improve the standard and equity of health services for all levels of society. one of the main obstacles that is often faced is the lack of management of patient queues that still use manual systems, causing long and irregular queues resulting in inefficient and ineffective patient waiting times. this research was conducted to build a more efficient and effective Banyumudal Health Center queue service system. by using the waterfall method, through this system, it is hoped that service efficiency will increase by reducing the duration of patient queues and improving better service quality. This method involves clear stages, starting from analyzing needs, designing designs, and testing. The results of the study show that the application of the waterfall method in the development of the Banyumudal health center queuing service system is able to improve queue management efficiently and effectively and provide information to patients regarding queue status, as well as facilitate health center officers and doctors in monitoring the queuing process. blackbox testing results show that all systems function properly according to predetermined specifications. thus, the queuing system designed is expected to have a positive impact on improving the quality of queuing services at the Banyumudal Health Center.
Autonomous Camera Tracking System Using Image Processing for Dynamic Educational Content Creation
In the context of the Online Learning activity, where video content plays a crucial role in educational materials, the demand for effective video production systems has become essential. Traditionally, at least two people are needed to operate cameras, which poses a challenge due to limited human resources. This study addresses this issue by developing a Camera Position Tracking System using image processing, specifically utilizing the MediaPipe framework for real-time tracking of presenters. The system's mechanics enable a DSLR camera to automatically adjust its position based on the presenter’s movement, detected within a range of 1.5 to 8 meters. The light intensity required for optimal operation is between 125 and 190 lux. The system's success lies in converting detected position data into motor stepper pulses that move the camera, ensuring efficient, cost-effective video production with minimal human intervention.
Optimization of Small-Scale Coffee Roasting Machine with Servo Temperature and Angle Control for Consistent Roasting Results
The coffee roasting process is essential for creating distinctive aromas and Flavors. Manual roasting often results in uncontrolled temperatures, resulting in uneven and burnt coffee beans. Therefore, an automatic roasting machine was developed to control stable temperatures at setpoints of 180°C (light roast), 220°C (medium roast), and 250°C (dark roast), with a monitoring system to ensure optimal results. Servo angle settings are used to optimize temperature stabilization, while a DC fan serves to remove excess heat from the machine. The system uses an Arduino Uno and ESP32, with a Thermocouple Type K temperature sensor and an I2C LCD display for real-time monitoring. Integration with IoT Blynk allows remote monitoring and control through a mobile application. Research shows that a servo angle of 140° provides the optimal temperature increase, while an angle of 100° is effective for lowering the temperature when it exceeds the setpoint. These angles are used in the system to keep the temperature controlled according to the specified target.
Application of K-Nearest Neighbor Algorithm for Consumer Behaviour Identification and Product Personalisation Based on Big Data Analysis
The rapid digital transformation has fundamentally altered the retail industry, presenting challenges such as shifting consumer behavior and intensified market competition. This research explores the application of the K-Nearest Neighbor (KNN) algorithm for identifying consumer behavior and developing product personalization systems based on big data insights. Utilizing a dataset comprising 10,000 transaction records from January to December 2023 and 5,302 product types, we implemented the KNN algorithm to predict consumer purchases. The data was processed into 89,908 distinct transaction records. Our evaluation, using 5-fold cross-validation, demonstrated that the optimal performance of the KNN model was achieved with ð‘˜=10, yielding a precision of 0.8319, recall of 0.8311, and an F1-score of 0.8312. These findings highlight the effectiveness of KNN in enhancing consumer satisfaction through precise product recommendations. This study provides strategic insights for modern retailers aiming to leverage AI and big data to remain competitive and meet evolving consumer expectations.
Copyright (c) 2024 Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Control of Multi-Robot Arms in Object Retrieval Based on Human-Machine Interface
Multi-robot arm control is the result of the development of advanced robotics technology. With the advancement in the field of human-machine interface, controlling robot arms has become more efficient and can be done intuitively by humans. In this study, we designed three robot arms of 4-DoF, each of which is controlled by a computer in a visual program interface. This research aims to develop a human-machine interface-based multi-robot arm control system that allows humans to interact with the robots directly. The movement method of each robot uses Trajectory Planning, which works when the operator gives motion commands through the interface display. Multi-robot communication with a computer using USB hub serial format. The computer is the master, and each Arduino on the robot is the enslaved. Three robot arms have been tested and controlled by the HMI computer, and all of them move according to the commands of the operator. The time required by each robot to complete its mission is ± 10 seconds. The results of this study are expected to open new opportunities in the application of robotics in various fields, such as the manufacturing industry, health services, and transportation.
Multi-Robot Arm; Human Machine Interface; Trajectory Planning
Enhanced Depth Control and Stability in Submersible Pylon Inspection Robots Using IMU-Based Extended Kalman Filter and PID Control
The research developed a Submersible Pylon Inspection Robot (SPIR) to clean and inspect underwater structures automatically, facing challenges in stability and depth of operation. Integrating the Inertial Measurement Unit (IMU) with the Extended Kalman Filter (EKF), as well as implementing customized PID controls, aims to improve the accuracy and stability of SPIR in dynamic underwater environments. The results show that the SPIR control system can follow the reference depth at shallow depths well, but has difficulty maintaining stability at deeper depths. The position error graph on the Z-axis shows the initial fluctuation that decreases over time, reflecting the increased calibration. The use of drive motors also shows different working patterns, with some motors active in depth settings and others for stabilization. This study shows that the integration approach of IMU, EKF, and PID control can improve SPIR performance, although further adjustments are required to meet the extreme challenges in underwater environments.