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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Design and Development of an Android-Based Application for Employee Leave and Absence Management at the Faculty of Science and Engineering, Bangka Belitung University
The process of submitting leave and absence management for employees of the Faculty of Science and Engineering, Bangka Belitung University, is still carried out manually using paper forms, potentially causing delays in information, recording errors, and difficulties in data archiving. This study aims to design and implement an Android- and web-based leave and absence management application system to improve the efficiency of personnel administration. The system development method used includes the stages of needs analysis, system design, implementation, and testing. The Android application was developed using Flutter, while the web-based system uses PHP with a MySQL database and Application Programming Interface (API) integration for real-time data measurement. This system provides features for submitting leave and permits, application history, verification and approval stages by superiors, employee data management, and application status notifications. The results of functional testing indicate that most features run according to system requirements, although there is one date logic validation test that does not meet expectations. Overall, the system developed is able to improve the efficiency of the administrative process, minimize recording errors, and support more structured, transparent, and integrated personnel data management.
Copyright (c) 2026 Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) http://creativecommons.org/licenses/by/4.0
Development of an Integrated Digital Audit System for Modular and Multi-Role-Based Higher Education Accreditation Document Management
Program accreditation is a strategic process in higher education that requires transparency, efficiency, and cross-unit collaboration. Common challenges include the complexity of document management, coordination between parties, and the potential for administrative errors. This research developed a web-based accreditation information system that is modular and supports various roles, namely administrators, study programs, the Institute for Learning Development and Quality Assurance (LP3M), and auditors. This system enables structured management of LED (Self-Evaluation Reports) and LKPS (Program Study Performance Reports), equipped with LP3M validation features, auditor comments, revision history, and audit trails to ensure accountability at every stage. The results of implementation show an increase in the efficiency of the accreditation process, a reduction in administrative errors, and an increase in transparency and accountability between units. Additionally, this system strengthens coordination between study programs and quality assurance institutions, making the accreditation process more integrated and controlled. Research findings confirm that this system is not only relevant for the developing institution but can also be replicated in other universities facing similar challenges. Thus, this web-based accreditation information system has the potential to be an innovative solution in supporting sustainable higher education quality management.
Optimization of Oyster Mushroom Dough Mixing Machine Using Omron CP1E PLC Control
Oyster mushroom cultivation is vital for providing the growing medium. Manually mixing the growing medium has several limitations, including time-consuming and inconsistent results. This paper objectives are to resolve growing medium oyster mushroom with mixing machine based on the Omron CP1E Programmable Logic Controller (PLC). The research methodology of mechanical and electrical of the machine was equipped with a single-phase AC motor, relay, control panel, and PLC-based control system to increases labor efficiency and ensures uniformity in the media mixture. This paper contribution research are to find the best composition of ingredients with PLC control to get homogenous media mixture by measuring the weight of the ingredients, mixing time, power consumption, and the homogeneity of the mixture. Based on the test results, the prototype is able to pack oyster mushroom growing media close to the initial mass, which is around 2975–3015 grams with an error of 1%, as well as decreasing power consumption due to the growing media mixture starting to become homogeneous so that the motor works lighter. The prototype of the oyster mushroom mixing machine has been successfully mix the media homogenous in 3minutes with the motor speed 70 rpm and power consumption 345 Watt.
Energy Audit and Optimization of Energy Consumption in the Electronics Manufacturing Industry based on ISO 50001:2018
The development of modern science and technology, especially in the field of industry. Currently, It will grow every year in line with the increasing demand for electricity. The increase will be directly proportional to the increasing needs and production targets in the Electronics Industry. PT XYZ is a manufacturing industry that produces electronic products will use quantitative methods based on the ISO 50001: 2018 framework in companies that consume fossil energy from PLN sources. Industries that have a land area of 25,552.76 m². In 2022 the total energy consumption of PT XYZ amounted to 8,133.08 MWh kWh with an average of 677.75 MWh per month and is expected to increase by 2% in 2023. This research will computer loads as the most widely used loads in the Electronics Manufacturing Industry. Therefore, this research will determine the value of Energy Consumption Intensity (IKE) and determine Energy Saving Opportunities (PHE) based on ISO 50001: 2018 to facilitate assessments, decisions, and quick actions of relevant parties in saving electrical energy in order to minimize waste of electrical energy in accordance with the principles of energy management. The savings generated by this application reach 77,839 kWh/m² per year and potential electricity cost savings of around Rp 170,780,234.63 per year
Design of an Automatic Relay-Based Switching System Using Battery and PV Voltage in Off-Grid Solar PV Lighting
The use of solar energy through off-grid photovoltaic (PV) systems to meet energy demands—particularly for DC lighting —still requires further development to address challenges such as weather variability and other limitations. Additionally, an effective control process for valve-regulated lead-acid (VRLA) batteries is crucial to prevent rapid degradation and shorten lifespan. This control ensures charging starts when the depth of discharge (DoD) limit is reached and prevents simultaneous charging and discharging. This study proposes an integrated off-grid PV lighting system with control features. The system uses a low-cost, relay-based automation approach, known as SOL-ARSAT (Solar PV Off-Grid Lighting System with Relay Switching Automation Technology). The system incorporates an AC power source as backup and applies three automatic switching controls based on battery and PV voltage. The results show that the system operates according to the designed control logic (logic 1 = active, 0 = inactive) and successfully manages power transfer between PV and AC sources. The control strategy prevents simultaneous charging and discharging, a prolonged low state of charge (SoC). As a result, the system improves lighting reliability and enhances battery protection, thereby extending the battery lifespan.
Design of a Mobile-Based Waste Management Application with a Waste Identification Feature as a Public Education Medium
The waste problem in Indonesia requires technological solutions to raise public awareness. This study aims to design a mobile-based waste management application as a medium for public hygiene education. Using engineering methods, it has four main features: waste type identification through camera scans, waste disposal management, digital waste management literacy, and a recycled product marketplace. The design stages include system specification analysis, interface design, and functionality testing. System testing results using the System Usability Scale (SUS) method involving 10 respondents showed an average score of 76.7. Based on SUS assessment standards, this score falls into the "Acceptable" category with an Adjective Rating of "Good" . This demonstrates that the waste identification feature makes it easier for users to recognize and sort waste independently, and all system functions perform according to design specifications. This application is expected to be an effective digital instrument in increasing environmental awareness and community independence in managing household waste.
Optimized PID Tuning in Pyrolysis Temperature Control Using Genetic Algorithm and Particle Swarm Optimization
Temperature control is crucial for maintaining stable and effective thermal treatment in pyrolysis system. For this application, Proportional-Integral-Derivative (PID) controller is frequently utilized due to its ease of use and efficiency. This study aims to evaluate and compare the performance of classical and metaheuristic tuning methods for PID controllers in pyrolysis temperature control. This work compares conventional Ziegler-Nichols (ZN) and Cohen-Coon (CC) methods with metaheuristic optimization techniques, specifically Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), for tuning PID controller parameters. The main contribution of this research is the demonstration of improved control performance and computational efficiency using PSO-based PID tuning for pyrolysis applications. Simulation results show that PID controllers that the parameters tuned by GA and PSO achieve faster and smoother responses, with small overshoot, compared to classical methods. From both methods, PSO provides balanced performance with the shortest rise time (30.66 s), fastest settling time (50.80 s), and lowest overshoot (1.15%). Although both GA and PSO can maintain the set point of 500 °C with satisfactory transient response, PSO also shows better convergence efficiency, with smaller iteration numbers and lower computational effort. The results indicate that PSO-tuned PID is suitable for pyrolysis temperature control applications.
Development of E-Tourism System for the Bangka Islands Using the Extreme Programming Method Towards Digital Tourism
Regional tourism often faces obstacles in providing fast, accurate, and easily accessible destination information to tourists. Many regions lack a digital platform capable of presenting information in an integrated manner, making it difficult for tourists to obtain an overview of tourist attractions, supporting facilities, and travel routes. This information accessibility problem affects the efficiency of tourism promotion and results in suboptimal implementation of digital transformation concepts. This study aims to develop and evaluate a E- Tourism application to improve the accessibility of tourism destination information and support digital transformation in the regional tourism sector. The system development was carried out using the Extreme Programming (XP) approach to ensure a fast iterative process, flexibility to respond to changing user needs, and software quality improvement in each testing cycle. Usability evaluation was conducted using the System Usability Scale (SUS) method involving 70 general user respondents. The test results show that the application obtained a SUS score of 75.74 in the acceptable category, indicating that the application is easy to use, clear, and aligned with tourism information needs.
Optimization of Smart Building Electrical Load Prediction Using Long Short-Term Memory
The advancement of smart building technologies requires energy management systems that are both efficient and capable of adapting to dynamic operational conditions. A key component of such systems is reliable electrical load forecasting, as building energy demand is affected by environmental conditions, occupancy behavior, and operational activities that exhibit nonlinear and time-dependent characteristics. This study explores the use of the Long Short-Term Memory (LSTM) approach for forecasting smart building electricity consumption based on multivariate time-series data. The input dataset incorporates temporal features, ambient temperature, humidity levels, occupancy-related patterns, and major electrical load components within the building. The research workflow consists of data preprocessing, normalization, time-series construction using a sliding window strategy, LSTM model training, and evaluation of forecasting performance. The findings indicate that the building’s electricity demand varies approximately between 6 kW and 17 kW, with an average load ranging from 11 to 12 kW. Performance assessment yields an RMSE of about 3 kW and a MAPE of roughly 25%. The largely symmetric error distribution around zero suggests minimal systematic bias in the predictions, although the model’s accuracy during peak demand periods remains limited.
Harmonic Distortion Assessment of Nonlinear Medical Loads in a Hospital Distribution Network Using ETAP Simulation
The growing use of power-electronics-based medical equipment has significantly altered the load characteristics of hospital electrical distribution systems. As nonlinear devices increase, harmonic distortion becomes a critical power quality concern that may affect equipment reliability and operational safety. This study investigates harmonic behavior in a 20 kV/0.4 kV hospital distribution network through harmonic load flow simulation using ETAP software. Total Harmonic Distortion of Voltage (THDv) and Total Harmonic Distortion of Current (THDi) are evaluated at selected buses and at the Point of Common Coupling (PCC), with reference to IEEE Std. 519-2014. Simulation results indicate that two low-voltage buses supplying high-capacity medical equipment exhibit THDv values of 8.21% and 6.74%, exceeding the recommended 5% limit. The THDi at the PCC reaches 14.37%, surpassing the allowable limit for the calculated short-circuit ratio (Isc/IL = 8.43). Dominant harmonic components are identified at the 5th and 7th orders, confirming the influence of rectifier-based medical systems and UPS units. The findings demonstrate that nonlinear medical loads significantly contribute to harmonic propagation, increased branch losses, and voltage distortion. Appropriate mitigation strategies, including harmonic filtering and load configuration adjustments, are therefore essential to ensure compliance with power quality standards and to maintain reliable hospital operation.
Analysis of Energy Management System and Feasibility of 25 kWp Rooftop Solar Power Plant using Techno-Economic Method in DKI Jakarta Regional Government Building
The building sector is a major contributor to energy consumption and greenhouse gas emissions in Indonesia, accounting for approximately 50% of national energy use and nearly 30% of total emissions. This study evaluates the implementation of an ISO 50001–based Energy Management Systems (EnMS) in a government building in Jakarta, combining energy efficiency retrofits with rooftop photovoltaic (PV) integration. The research contributes a comprehensive technical and economic assessment that quantifies energy savings, emission reductions, and financial feasibility within a replicable public-sector framework. The methodology included an ISO 50001–aligned energy audit, building energy simulation using DesignBuilder, PV system design with PVsyst, and economic feasibility analysis. LED lighting retrofits reduced lighting energy consumption by 38.14%, while air-conditioning optimization improved thermal comfort. A 24.75 kWp rooftop PV system generated 33,428 kWh annually, supplying 17.97% of the building’s electricity demand. In total, the integrated measures achieved annual energy savings of 37,587 kWh and reduced emissions by 31.57 tons of CO₂. Economic analysis indicated that the project was financially feasible, with a positive NPV, a 6% IRR, an 8.18% ROI, and a payback period of approximately 14 years. The integrated approach proved effective and showed strong potential for replication in similar public buildings.
Microwave Sensing of Sugar Solution Concentration Using a 2.4 GHz Microstrip Antenna
Microstrip antennas are widely used in sensing applications according to compact, low-cost, and easy to fabricate. This study presents the design and evaluation of a 2.4 GHz circular patch microstrip antenna integrated with a split-ring resonator (SRR) for sensing sugar-solution concentration through dielectric property induced perturbations. The antenna employs an inset feed configuration and is implemented on an FR4 substrate. The design and parametric analysis are carried out in simulation by placing sugar solutions with mole fractions from 0 to 0.04 in the sensing region. In result, we observe changes in resonant frequency, minimum return loss, and quality factor (Q). The simulations indicate monotonic trends with concentration, with the minimum return loss becoming less negative as concentration increases, accompanied by reductions in resonant frequency and Q. Experimental measurements of the fabricated prototype, however, show weaker and less consistent correlations across the same parameters, highlighting the sensitivity of the response to practical factors such as sample positioning, fabrication tolerances, and measurement repeatability
Intelligent Fault Detection In a 25 MVA Transformer Using ANFIS
This study aims to develop an intelligent fault prediction model for a 25 MVA power transformer using the Adaptive Neuro-Fuzzy Inference System (ANFIS), to improve classification accuracy and ensure selective, reliable protection decisions in power systems. The research is grounded in the limitations of traditional differential relay protection, which struggles to distinguish between internal and external faults during transient conditions. ANFIS combines fuzzy logic’s ability to handle uncertainty with the adaptive learning of neural networks, making it a suitable tool for non-linear fault data analysis. A simulation was carried out in MATLAB/Simulink. Current signals from CTs on both primary and secondary sides served as input features. The model was trained using 270 data samples and tested with 30 samples. Two membership functions generalized bell-shaped (Gbell) and triangular (Tri) were evaluated. RMSE was used as the performance metric. The ANFIS model with Gbell MF yielded a lower RMSE (0.0116) compared to Tri MF (0.0445), indicating better prediction accuracy and stability. The system consistently identified internal faults (output 1), and external faults (output 0) based on a 0.5 decision threshold. The findings validate the potential of ANFIS for integration into digital relay systems, enhancing real-time transformer protection through adaptive learning.
Adaptive Neuro-Fuzzy Inference System (ANFIS)
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.
Design and Operational Evaluation of Off-Grid Solar Power Plants with Integrated Automatic Cleaning Systems for Enhanced Performance
This study details the design and experimental evaluation of an off-grid photovoltaic (PV) system equipped with an automatic solar panel cleaning mechanism to address performance degradation due to dust accumulation. The system integrates a mechanical wiper-based cleaning unit, solar charge controller (SCC), inverter, and low-voltage disconnect (LVD) to maintain reliable and stable operation in stand-alone settings. Experimental tests were performed on a 50 Wp PV module under actual outdoor conditions in Padang, Indonesia. System performance was assessed before and after panel cleaning using key electrical parameters, such as output voltage, current, output power, and relative efficiency improvement. Results show that the automatic cleaning mechanism increased the average PV output power from 0.88 W to 1.71 W, representing an efficiency improvement of approximately 11.89% compared to the uncleaned state. In contrast to previous studies that focus on grid-connected systems or manual cleaning methods, this research introduces a low-cost, self-operating cleaning solution tailored for small-scale off-grid PV applications in tropical environments. The proposed system offers practical benefits for enhancing energy yield, system reliability, and maintenance efficiency in remote solar installations.
Design of Sepic Converter as Battery Charger with Artificial Neural Network - PID Method for Load Variation
More adaptable charging methods are required as a result of the growing variety of electronic gadgets that use rechargeable batteries brought about by technological advancements. When trying to charge different battery types with a same charger, differences in battery parameters, like voltage and capacity, present difficulties. This study suggests an adaptive charging system that can charge several battery types using a single port connection in order to solve this problem. To transform a 24 V DC input into an output voltage appropriate for the particular battery requirements, the system uses a SEPIC converter whose duty cycle is controlled by a microprocessor. The duty cycle rises until a specific current level is measured when a battery is attached and the limit switch is activated. The measured voltage and current data are then processed by an Artificial Neural Network (ANN) algorithm to determine the battery type and set the appropriate charging voltage setpoint. After that, a PID controller is used to keep the charging conditions steady. LiFePO4 (12.8 V, setpoint 14.6 V), Li-ion (14.8 V, setpoint 16.8 V), and Lead Acid (12 V, setpoint 14.4 V) batteries were used to test the system. The system successfully charged all three battery types with an average error of 0.174%, according to experimental findings, demonstrating precise and reliable control performance.
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%.