We would like to inform you that Volume 14, Number 2, and earlier issues of Energy: Jurnal Ilmiah Ilmu-ilmu Teknik are available on the old system at the following link: https://ejournal.upm.ac.id/index.php/energy/. This is due to technical issues caused by a recent hacker attack, which has prompted us to create a new, more secure system for future publications. As a result, issues from Volume 15, Number 1 onwards will be published on the new system at: https://e-journal.upm.ac.id/index.php/energy/. We appreciate your understanding and cooperation during this transition, and we sincerely apologize for any inconvenience caused.
Designing Solar Power Plants as a Source of Electricity for Insect Traps
This study proposes the design and evaluation of a solar-powered insect trapping system as an environmentally friendly solution for pest control in agricultural fields. The system integrates a photovoltaic (PV) module as the primary energy source with a microcontroller-based control unit. A Passive Infrared (PIR) sensor is employed to detect insect movement, while an electric grid mechanism is used for pest eradication. The system is controlled using an Arduino microcontroller to ensure synchronized operation between detection and execution components. The research methodology involves system design, hardware and software implementation, and field testing in rice cultivation areas. Experimental results indicate that the device provides an effective illumination radius of approximately 5 meters and successfully captured 87 insect pests within two days of operation. Furthermore, the system demonstrates stable energy performance, with efficient battery charging during the daytime and reliable operation at night. These findings confirm that the proposed solar-powered insect trap is a viable, sustainable, and eco-friendly alternative to conventional pesticide-based pest control methods. Future work will focus on optimizing light intensity, improving sensor accuracy, and integrating ultraviolet light to enhance insect attraction.
Copyright (c) 2026 ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK https://creativecommons.org/licenses/by-nc/4.0
Enzymatic Conversion of Biomass to Biofuels: Process Mechanisms, Enzyme Optimization, and Industrial Challenges
Biomass conversion to biofuels has gained significant attention as a sustainable alternative to fossil-based energy, with enzymes playing a crucial role in enhancing process efficiency and selectivity under mild operating conditions. This review article examines the roles of key enzymes, including cellulases, hemicellulases, amylases, lipases, and laccases, in lignocellulosic hydrolysis, lignin structure disruption, and lipid esterification and transesterification reactions, enabling the production of bioethanol and biodiesel under milder operating conditions with high selectivity. Comparative insights are provided to highlight the relative performance of these enzymes in terms of conversion efficiency, substrate specificity, operational stability, and tolerance to process conditions, as reported in recent studies. The review further examines enzyme optimization strategies, including immobilization techniques, protein and metabolic engineering approaches, and advanced bioreactor configurations, which have been shown to improve enzyme reusability and overall process productivity. Quantitative performance indicators reported in the literature, such as biofuel yields and conversion efficiencies, are critically analyzed to assess the feasibility of enzymatic routes compared to conventional chemical processes. Finally, key industrial challenges related to enzyme cost, stability, and scalability are discussed, along with emerging technological pathways that support the potential industrial implementation of enzymatic biomass conversion for biofuel production.
Nonlinear Trade-Off Between Agitator Speed and Biodiesel Quality in Transesterification: A Lab-Scale Study
The agitator speed controls the intensity of interaction between the immiscible oil and methanol phases during transesterification. This, in turn, shapes the overall reaction environment during the biodiesel production process. While higher agitation rates are often associated with increased mass transfer, their impact on the resulting fuel properties is not always proportional. In a controlled laboratory setting, the effect of agitator speed was examined at 300, 500, 700, and 900 rpm, with particular attention paid to biodiesel yield, density, kinematic viscosity, and flash point. A gradual shift in system behavior became apparent as the agitation rate increased. In the intermediate range of 500–700 rpm, the process tended to stabilize, producing biodiesel with relatively consistent characteristics. The measured kinematic viscosity was between 4.42 and 4.45 cSt, accompanied by a density of approximately 861 kg/m³. However, pushing the system to higher agitation rates led to a different response. At 900 rpm, the yield dropped sharply to 49.53%, and the viscosity increased to 4.92 cSt. This behavior indicates the onset of unfavorable hydrodynamic conditions, where intensive mixing likely disrupts phase separation and promotes the formation of a stable emulsion. Meanwhile, the flash point continued to increase from 124.7 °C to 166.8 °C, indicating a progressive decrease in residual methanol. Overall, these observations suggest that the influence of stirrer speed is governed by competing mechanisms rather than a simple monotonic trend. Operation in the 500–700 rpm range appears to offer a more reliable compromise, where conversion and fuel properties remain balanced. From an engineering perspective, this range provides a useful reference for establishing operating conditions in biodiesel reactors, especially when considering process development beyond the laboratory scale while maintaining consistent product quality.
Design and Development of a Two-Tub Washing Machine Trainer Based on Arduino Nano
A washing machine is a crucial device for society as it offers convenience and practicality. However, the efficiency of a washing machine can decline over time, especially in its components which may experience performance degradation or damage. This research involves designing a damage detection tool for washing machines, structured as a trainer operated in simulation form, serving as a learning medium to better understand the systematic functioning of washing machines. This trainer module uses toggle button switches installed on each cable line to simulate various damage conditions. The sensor used in this trainer is the PZEM-004T, which detects the current, voltage, and power used by the AC (Alternating Current) motor. To measure the motor's RPM (Revolutions per Minute) speed, a proximity sensor utilizing the Hall effect principle is employed. The microcontroller used to process the data generated by the sensors is an Arduino Nano, with the data displayed on an LCD (Liquid Crystal Display). In this research, the results based on the PZEM-004T sensor testing showed it could measure voltage, current, and power with an error rate of 7.3% and a success rate of 92.7%. The proximity sensor could measure motor speed with an error rate of 3.4% and a success rate of 96.6%. The main challenge in the monitoring system was the real-time reading on the LCD screen frequently halting due to the long delay required to read the proximity Hall effect sensor values.
Copyright (c) 2024 ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK https://creativecommons.org/licenses/by-nc/4.0
DC Motor Settings Using Zigler Nichols PID Tuning as an Interactive Learning Media
DC Motor is a direct current that is often used in everyday life that uses speed regulation, the DC Motor rotation will be given a load so we test the Motor rotation value according to the weight of the motor load that is generated after the Motor is activated. To find out the motor rotation and the result ing value after being given a load, we are here using the Arduino Mega component as a microcontroller, the IBT 2 driver as a DCb motor speed controller that has been given a load, the encoder as a copy of the old motor rotation data to the new motor data, the potentiometer as a sensor to find out DC Motor rotation, LCD to display data that has been taken, Arduino Ide as Software. And the control used is PID (proportional integral differential). This PID control system works by processing calculations based on the control variables Kp, Ki, and Kd to achieve conditions according to the expected setpoint.
Development Of Internet Of Things (IoT) Trainer As A Learning Media Using NodeMCU ESP32CAM
This study examines the potential and implementation of feature development on the ESP32CAM as an Internet of Things (IoT) based learning medium in the form of a trainer. This research addresses the gap in the use of the Node MCU ESP32CAM as IoT technology in educational media, which has not been widely utilized. The primary goal of this study is to analyze and explore the use of the ESP32CAM as a trainer to enhance IoT - based learning. The study employs an exploratory approach to investigate the use of the ESP32CAM, including an analysis of the application of the technology in a learning environment. Data were obtained through questionnaires distributed to experts and users/students, involving 45 students from the Elect rical Engineering program at Trunojoyo University Madura. The results of the study indicate that the IoT trainer using the Node MCU ESP32CAM is highly feasible, with an eligibility percentage of 91.08% from expert evaluations and 87.25% from user evaluations. It is hoped that the findings of this research can provide new insights into innovations in IoT use and serve as a foundational basis for further development in the related field
Automation System For Sorting Goods In The Production Room Using Scada and PLC
The development of the industrial revolution is progressing. Especially on production performance or machine parts. Industrial revolution 4.0 uses the internet and digitalization. So there are lots of new innovations. In a large - scale company, of course there are many tools and machines that need to be regulated whether they are on or not with regular supervision. With regular supervision, it is impossible for human workers to check one by one, there by wasting time and reducing production levels. Therefore, it is necessary to develop a control system using PLC and HMI (Human Machine Interface) as the brain or control center for the company. In the industrial sector, PLC (Programmable Logic Controller) is an important factor in the operation of automatic mach ines in factories replacing relay control systems. So that PLC as a control system in the industrial sector can move machines according to needs. One part of the industry is the production room. The production room is the part where there are manufacturing materials or goods up to packaging. This research aims to design and implement a PLC (Programmable Logic Controller) and SCADA by adding sensors and actuators as output. The method used is a rule base system, the system runs according to a predetermined sequence and flow. The results of this research are the PLC, the SHT 20 temperature and humidity sensor can produce temperature and humidity values, the capacitive photosensor can detect items with 35 trials accurately but the distance is limited to only 27cm, the proximity sensor can only detect metal objects by attaching to the sensor and The actuator in the form of a stepper motor can run according to the commands given and is well integrated into the HMI (Human Machine Interface).
Internet Of Things (IoT) Based Soil Leveling and Compaction Prototype
The purpose of this research is to design a prototype of a soil leveling and compaction tool based on the Internet of Things (IoT). Currently, many projects still rely on manual tools for soil leveling and compaction, which can result in reduced effectiveness, lack of safety for workers, and high levels of fatigue. Therefore, this tool is equipped with ESP32-Cam, DC Motor, and BTS 7960 Motor Driver, and will be operated remotely via a smartphone's Android remote control, utilizing IoT technology to enhance efficiency and accuracy in soil leveling and compaction. By three trials result on sandy soil showed a more significant reduction, with an average of 3.6 mm in 4 seconds, compared to rocky soil, which had an average reduction of 3.3 mm in 5.3 seconds over three trials.
Drip Irrigation System for Chili Plants Using Sensor Arrays to Detect Soil Moisture
Drip irrigation is an irrigation technology that aims to efficiently utilize a very limited water supply and increase the effectiveness of water use. One of the plants that can apply a drip irrigation system is the chili plant. To produce chili plants with good quality, soil moisture in chili plants needs to be considered, the soil moisture needed is 60%. This tool uses the ESP 32 MCU Node as a microcontroller. This research will design a soil moisture control system in chili plants using a Proportional Integral Derivative (PID) controller. The system works automatically to control soil moisture in chili plants in order to maintain the desired moisture value, which is with a soil moisture value of 60%. Currently there are still many farmers who apply watering manually, this can cause the use of water that is not in accordance with the needs of plants. From the problems that often occur, an automatic watering innovation was created by applying the drip irrigation system method controlled by a series of soil moisture sensors and other electronic devices. From the test results show that the tool will water with a drip irrigation system when the soil moisture of chili plants is below the setting point which is 60%
Design and Development of Solar-Powered Water Pump Installation for the Tauno Village Community, Oba Tengah District, Tidore Kepulauan City
Water is a fundamental human necessity, essential for daily activities such as drinking and cooking. However, access to water can be problematic, especially in areas where water sources are limited or groundwater is far from residential areas. Although various water pumps are now readily availab le, the challenge often lies in the availability of power sources. Fortunately, in tropical regions, sunlight is freely available year round. To generate electricity, sunlight must first be converted through an energy conversion process before it can be used to power devices such as water pumps. Therefore, it is necessary to calculate the clean water needs for Tauno Village in Oba Tengah District, Tidore Kepulauan City, which has a population of 516 people. The daily water requirement per person is 60 liters, resulting in a total village water demand of 32,506.85 liters. The total water requirement for all public facilities is 90,037.385 liters. Consequently, a 7,500 W pump with a flow rate of 400,000 liters per day and a head of 10 meters is selected to meet the clean water needs of Tauno Village. To supply power to the pump, 16 photovoltaic panels, each with a capacity of 1,200 Wp, are required.
Comparison of K-Nearest Neighbor Algorithm and Logistic Regressionin the Classification of Cervical Cancer Disease
in the face of the globalization era that is increasingly competitive, a company is required to be able to devise competitive in order to survive and win the competition. Because it needed a solution to improve the quality of the product so that it can assist in winning the competition with its competitors. PT. Indonesia Timber Kutai (ITC) as a company engaged in lumber and plywood production was should be ableto survive in an increasingly tight competition.Plywood is formed by layers of sheets –sheets of wood called veneer. The quality of the veneers will effect the quality of plywood produced by PT Indonesia Timber Kutai. To get a good veneer quality then needed a good combination between the blade with the machine. Researchers do research on the condition of the blade. A place for pengashan blade is subsi GrindeThe cause of the majority of the knife is a blunt knife quickly, so the quality of the producedveneer would be ugly. Researchers try to find problems –problems encountered and immediately make the effort improved sharpening results with seven quality control. For the results of his research is before there is an improvement obtained 22 case knife quickly dulled from 72 blade, after no improvement, found only 1 case of only fast knife dulled from 72 blades
Improving the Quality of 5 Feet Knife Sharing in Subsi Grinder with Seven Quality Control Tools (Case Study at PT KUTAI TIMBER INDONESIA)
In the face of the globalization era that is increasingly competitive, a company is required to be able to devise competitive in order to survive and win the competition. Because it needed a solution to improve the quality of the product so that it can assist in winning the competition with its competitors. PT. Indonesia Timber Kutai (ITC) as a company engaged in lumber and plywood production was should be able to survive in an increasingly tight competition. Plywood is formed by layers of sheets- sheets of wood called veneer. The quality of the veneers will effect the quality of plywood produced by PT Indonesia Timber Kutai. To get a good veneer quality then needed a good combination between the blade with the machine. Researchers do research on the condition of the blade. A place for pengashan blade is subsi Grinde The cause of the majority of the knife is a blunt knife quickly, so the quality of the produced veneer would be ugly. Researchers try to find problem problems encountered an immediately make the effort improved sharpening results with seven quality control. For the results of his research is before there is an improvement obtained 22 case knife quickly dulled from 72 blade, after no improvement, found only 1 case of only fast knife dulled from 72 blades.
Prototype of Automatic Railway Crossing Doors Using LoRa RFM 95 Communication
Railway crossing gates are railway facilities or infrastructure to protect train travel and provide warnings to road users. The prototype of this automatic railway crossing gate uses an Arduino Nano, LoRA RFM 95, 5 kg Load Cell, MG996R Servo Motor, LED, and Buzzer. In component testing there are Load Cell, LoRa RFM 95, and MG996R Servo Motor tests. In the LoRa RFM 95 test, it was successful up to a distance of 350 meters, beyond this distance it failed to transmit the signal. Tests such as RSSI, SNR and Delay were also carried out. In the LoRa test, slave1 data was produced -34 to -104 (dBm) at a distance 0 –350 meters and slave 2 data produced (-32 to –107) (dBm) at a distance of (0 –350) meters but at a distance 400 –450 but each slave cannot send, the SNR on slave 1 has 8 data including (9.50 –4.50) dB and slave 2 (9.50 –3.00) dB which is relatively low and the delay of sending depends on the distance and obstacles to sending. Testing the MG996R Servo Motor showed an error (0.07%). Load Cell testing shows errors on Slave 1 (0.27%), Slave 2 (0.07%), and Master (0.20%). And the overall system test shows success and in opening or closing the door latch it can work properly.
Design and Development of an IoT (Internet Of Things)-Based Temperature and Humidity Control System for Hamster Cages
Hamsters are generally healthy creatures and can live about two years or more. They need a comfortable cage with a temperature of 17oC to 23oC and for humidity is 40 RH% to 70 RH% which sometimes these things are neglected by hamster owners. If the temperature and humidity are not appropriate it can cause disease in hamsters even to the death of hamsters. So a tool is needed to stabilize temperature and humidity. In this system using the method (Hybrid Proportional Integral Derivative - Artifical Neural Network (PID-ANN) where the method is a combination of PID and ANN methods as a determinant of PID parameters, namely Proportional Constants, Integral Constants and Derivative Constants automatically with the help of ANN tuning. as temperature and humidity stabilizers. The inputs in this method are temperature and humidity obtained from the DHT22 sensor. While the output in this study is in the form of analog values for dimmer control controlling lux on incandescent lamps and humidifiers. This system is also based on the internet of things so that it can be monitored and controlled in real time. So that it can be used anywhere and anytime
Experimental Study of Nozzle Hole Diameter and Air Volumetric Flow Rate on Flame Temperature of Used Oil-Fired Stove
The utilization of used oil as fuel has begun to be used today even though only some people. Knowing how the interaction of nozzle hole diameter on fire temperature in portable stoves. This study used experimental research, by testing the value of the independent variable with (nozzle hole diameter (2, 3, 4) and variation of air volumetric flow rate, the response obtained (dependent variable) knowing the causal relationship of the study. This research processing method uses factorial ANOVA. see the interaction between independent variables on the dependent variable in addition to seeing the influence of independent variables independently on the dependent variation. The flame that produces the highest temperature is 900C in the 3mm hole diameter variation with an airflow rate of 0.004 mᶟ/s. The flame with T1 varies the diameter of the 4mm hole with an airflow rate of 0.006 mᶟ/s. Then the T2 flame has decreased graphically from the previous diameter at 3 mm hole diameter with air volumetric flow velocity at 0.006 mᶟ/s. The larger the hole, the smaller the air pressure, otherwise the smaller the diameter of the nozzle hole, the greater the pressure spread into the combustion chamber is better.
Test the Effect of Adding a Cyclone on the Quality of Liquid Smoke
Bintaro fruit is a drupa (seeded) fruit with lignocellulosic fiber resembling a coconut. The presence of cellulose content makes bintaro fruit potentially in the manufacture of bioethanol through a hydrolysis process that breaks down cellulose into glucose which is the raw material for bioethanol fermentation. Pyrolysis is a process of heating a substance in the absence of oxygen resulting in the decomposition of hardwood constituent components and producing substances in three forms, namely solid, liquid and gas. Pyrolysis has been used since ancient times to turn wood into charcoal on an industrial scale. This research is using experimental method. The experimental method is used to determine the effect of using a cyclone on the pyrolysis process. The final result is liquid smoke whose characteristics will be compared before and after the installation of the cyclone. The effect of pyrolysis temperature on liquid smoke can affect the resulting liquid smoke yield. Temperature and time can have an important effect on increasing the liquid smoke yield to conditions where gas production that is difficult to condense will lower the liquid obtained, so that further increases in temperature and time will reduce the liquid smoke yield. In the addition of cyclones to pyrolysis which aims to produce a clear liquid quality. In testing the addition of a cyclone to pyrolysis, it can produce clear liquid coming out of the condenser compared to a cyclone which produces a dark black color. It should be noted and tested first to find out the occurrence of leaks in the reactor tube and also pay attention to the raw material for Bintaro fruit so that it dries first before carrying out further research. It is necessary to check before conducting research on the temperature sensor cable so that it is safe not to be exposed to hot coals in order to get efficient results.
Performance Optimization Analysis of a 20 Kilo Volt (kV) Distribution Network in Dili City Using ETAP Software
The 20 kV power distribution network in Dili City faces technical challenges in the form of voltage drop and relatively high feeder loading levels, particularly on feeders with long distribution routes. The Dili City distribution network has a configuration centralized to a single power supply source, namely the Camea Substation, which limits the ability to transfer loads. This research aims to analyze the existing condition and to evaluate the effect of adding a new substation in the Comoro area on improving network performance. This research uses a power flow simulation–based approach employing ETAP software. The results show that under existing conditions, buses at the end of the lines experience voltage drops below the allowable standard of up to 14.30%, and four feeders have loading levels exceeding 75%. The addition of the Comoro Substation and network reconfiguration significantly improve the voltage profiles of the distribution system, ensuring compliance with SPLN 72:1987. The loading level of the Camea Substation decreases to 72% of its capacity due to the reduction of feeder load, increasing the capability for load transfer and accommodating future load growth.
Analysis of Fuel Spray Characteristics of Pertalite, Pertamax, and Pertamax Turbo with Ethanol Blending
In the automotive industry sector, technological advances have entered the stage of using alternative fuels, and the principle of fuel injection in gasoline engines (electronic fuel injection), to create efficient fuel use and more environmentally friendly combustion. The method used in this research is an experimental method, namely a method used to test the characteristics of gasoline fuel with ethanol against spray using an injector. In this research, we will compare the characteristics of Pertalite, Pertamax, Pertamax Turbo gasoline spray, a mixture of ethanol and gasoline in different mixture variations. This test aims to analyze spray tip penetration, spray angle, and velocity of spray. The results of collecting spray tip penetration data resulted in the highest data value for Pertamax Turbo fuel mixed with 7% ethanol and the lowest for Pertalite fuel mixed with 7% ethanol. The results of the spray angle data collection had the highest value in the Pertamax 10% ethanol mixture and the lowest in the 5% ethanol mixture with Pertamax Turbo fuel. From the results of the Velocity of spray data processing, the highest value was found in the 10% ethanol mixture with Pertalite fuel and the lowest was the 5% ethanol mixture with Pertamax Turbo fuel. For ethanol mixtures, more attention must be paid to the complete spray or misting of the injected fuel. Mix the fuel with ethanol according to applicable standards. Always pay attention to chamber equipment to avoid leaks when collecting data
Design and Testing of a Milliampere Scale Leakage Current Sensor Based on a Current Transformer for Substation Lightning Protection
Leakage current in lightning arresters is an important indicator of insulation conditions and protection system performance in substations, so a measurement method capable of detecting currents in milliamperes accurately and stably is required. This study aims to design and test a milliamperes-scale leakage current sensor that can be used for lightning arrester monitoring. The developed sensor is based on a current transformer with an analog signal amplification and filtering circuit, and data acquisition using a microcontroller. Testing was carried out experimentally by varying the resistive load and the number of turns, then the measurement results were compared with an AVO meter as a reference measuring instrument. The test results showed that the sensor was able to measure leakage current with a relatively low error rate, where the lowest error occurred at a load of 33 Ω and increased at larger loads due to a decrease in current. The relationship between current and load variation showed a linear characteristic with a coefficient of determination (R²) value close to 1. In addition, magnetic field analysis showed that the relative permeability value of the ferrite core was in the range of 88.4 to 98, which reflects the stability of the core's magnetic properties under various test conditions. Based on these results, the developed sensor has the potential to be used as part of a lightning arrester leakage current monitoring system to support the maintenance and reliability of the substation protection system.
An Epistemological Analysis of Metaheuristic MPPT Performance for Photovoltaic Systems under Partial Shading Conditions
Metaheuristic-based maximum power point tracking algorithms are widely used in photovoltaic systems to address nonlinear and multi-peak characteristics under partial shading conditions. However, many reported performance claims rely mainly on numerical simulation and therefore require cautious interpretation. This study presents a simulation-based comparative and epistemological analysis of Particle Swarm Optimization and Differential Evolution for photovoltaic maximum power point tracking. Both algorithms are implemented in an identical buck converter-based photovoltaic framework to ensure fair comparison. Performance is evaluated under uniform irradiance and partial shading conditions using convergence time and tracked power as evaluation metrics. The results show that under uniform irradiance, both algorithms reliably converge to the maximum power point with similar steady-state accuracy, while Particle Swarm Optimization converges faster. Under partial shading conditions, Particle Swarm Optimization consistently tracks the global maximum power point, whereas Differential Evolution shows occasional convergence failure or suboptimal tracking. From an epistemological standpoint, these findings constitute coherent and pragmatically useful model-based knowledge, while remaining provisional due to the absence of experimental validation.
Copyright (c) 2025 ENERGY: JURNAL ILMIAH ILMU-ILMU TEKNIK https://creativecommons.org/licenses/by-nc/4.0
Sentiment Analysis of YouTube Comments Using the K-Nearest Neighbors (KNN) Method from an Axiological Perspective
The rapid development of social media as a space for digital interaction has increased the need for sentiment analysis to understand public opinion in a systematic and measurable way. This study analyzes YouTube comment sentiment using the K-Nearest Neighbor (K-NN) method while also examining the axiological value of applying this technology in support of a more ethical digital ecosystem. The dataset consists of 8,200 YouTube comments obtained from Kaggle without predefined sentiment labels. The data were preprocessed through case folding, tokenization, stopword removal, stemming, and normalization. Initial sentiment labels were generated automatically using K-Means clustering to form two classes—positive and negative—and were partially verified manually. The labeled data were split into training and testing sets with ratios of 50:50, 60:40, 70:30, and 80:20, and evaluated using K-NN with k values of 3, 5, 7, and 9. Model performance was assessed using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The results show that accuracy ranges from 0.95 to 0.96, with the best performance achieved at a 70:30 split and an optimal k value yielding 0.96 accuracy. Beyond technical contributions, this study highlights the ethical and practical value of sentiment analysis for interpreting public opinion, supporting fairer content moderation, and improving communication quality in social media environments.
Analysis of System Reporting and Validation in DC Microgrid DSC Research: An Ex Post Facto Reproducibility Study
Distributed secondary control (DSC) is essential for voltage regulation and current sharing in DC microgrids with high renewable penetration. However, the diversity of system configurations, control strategies, and validation approaches challenges the reproducibility of published results. This study evaluates reporting and validation practices in 74 DSC-related articles from a reproducibility and research ethics perspective. Using a document-based ex post facto design, we construct a Reproducibility Readiness Index (RRI) based on system configuration reporting, validation completeness, and performance metric clarity. Results show that most studies exhibit low to medium reproducibility readiness, with only about one third achieving high levels. While system descriptions are generally adequate, validation setups and performance metrics are often incomplete or qualitative. Studies including hardware-in-the-loop or prototype experiments tend to score higher, though weak documentation remains a major limitation. These findings emphasize reproducibility as both a technical and ethical concern and support the need for stronger transparency and open science practices in DSC research on DC microgrids.
Risk Factors Causing Occupational Accidents Using the FMEA and Fishbone Methods in the Particle Board Division of PT. Kutai Timber Indonesia
Occupational Health and Safety (OHS) is an essential aspect of industrial operations, aimed at preventing workplace accidents and maintaining a safe and productive environment. The Particle Board Division of PT. Kutai Timber Indonesia faces high accident risks due to heavy machinery and high-temperature processes. This study evaluates potential occupational hazards using the Failure Mode and Effects Analysis (FMEA) and Fishbone Diagram methods. FMEA is used to prioritize risks based on the Risk Priority Number (RPN), while the Fishbone Diagram identifies the root causes of critical hazards. The highest identified risk is the absence of an emergency response team in each shift (RPN = 148.5). Other major risks include inadequate monitoring of corrective actions, poor documentation systems, low employee involvement in hazard identification, and insufficient technical controls. Recommendations include forming emergency response teams, conducting regular safety training, improving documentation systems, and enhancing technical and administrative controls. Implementing these measures is expected to reduce accident rates and strengthen the safety culture in the company.
Geochemical and Mineralogical Analysis of Mining Tailings in Mimika Regency for Reutilization Potential Evaluation
This study characterizes the geochemical, mineralogical, and morphological properties of mine tailings along the Kali Kabur River in Mimika Regency, Central Papua. The tailings, generated by mining activities, contain valuable metallic minerals, including iron (Fe), copper (Cu), and titanium (Ti). Using X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), and Scanning Electron Microscope–Energy Dispersive X-Ray Spectroscopy (SEM–EDS), we identified major oxides (Fe₂O₃, SiO₂, CaO) and minerals (quartz, magnetite, ilmenite, chalcopyrite). Results indicate that the tailings possess potential for reutilization as secondary resources for metal extraction and as raw materials for iron sand production. This research provides novel insights into sustainable tailings management and offers guidance for local industries in the reutilization of mining waste, contributing to circular economy practices.
Implementation of Static Code Analysis to Detect Vulnerabilities in Applications Developed with the Assistance of Large-Language Models (LLM)
The emergence of large language models (LLMs), such as ChatGPT and GitHub Copilot, has transformed software development, including in higher education. Students can now easily create PHP code for Laravel web applications. This research implements static code analysis with PHPStan to detect security vulnerabilities in student-developed PHP code that is likely assisted by LLMs. The analysis was performed on the full code of 28 capstone projects, focusing on student projects that demonstrated patterns consistent with heavy LLM output use. The results show that 64.16% of LLM-assisted code often neglects data sanitization, uses raw queries without parameterization, and contains vulnerable authentication logic. This study contributes to web application security literacy for students and recommends static analysis as a pedagogical and preventive tool.
Comparison of Energy Obtained from Solar Panels in Partial Shading Condition Using Various MPPT Techniques
Partial shading conditions (PSC) create multiple peaks on the power–voltage (P–V) curve of photovoltaic (PV) systems, making it difficult for conventional Maximum Power Point Tracking (MPPT) algorithms to accurately identify the global maximum power point (GMPP). This study compares the performance of three MPPT techniques—Perturb and Observe (PNO), Global Maximum Power Point Detection (GMPPD), and the Four-Section (4S) method—by analyzing the electrical energy obtained during sudden changes in irradiance and shading. Experiments were conducted on two series-connected polycrystalline modules equipped with bypass diodes under three shading scenarios, with measurement data processed using an Arduino-based system. The novelty of this work lies in its experimental, energy-based comparison of PNO, GMPPD, and the recently developed 4S method under sequential irradiance transitions, providing a practical performance assessment that goes beyond instantaneous tracking evaluation commonly reported in previous studies. The results show that the 4S method significantly outperforms both PNO and GMPPD by providing faster tracking, lower computational demand, and superior accuracy under dynamic shading conditions. The total energy obtained using the 4S, GMPPD, and PNO methods was 4203.08 Wh, 3551.69 Wh, and 3091.60 Wh, respectively. These findings demonstrate that the 4S method offers the most efficient and reliable MPPT performance for PV systems operating under rapidly fluctuating environmental conditions.
Design of a Hydraulic System for a Glycerin Waste Mixer Machine Using Finite Element Method
This study presents the design of a hydraulic-based glycerin waste mixer machine, intended for use in the cement industry as a sustainable alternative to coal. Glycerin waste, a byproduct of biodiesel production, has a calorific value of 25,175.98 kJ/kg, making it a viable substitute fuel. However, its high viscosity and tendency to solidify at low temperatures pose significant challenges for processing. This research addresses these challenges by designing a hydraulic mixer with structural strength verified through Finite Element Method (FEM) analysis. The design follows the Ulrich & Eppinger product design approach, including concept development, technical specifications, and hydraulic system planning. Using Autodesk Fusion 360, the machine's frame, made of ASTM A36 steel, withstood loads with a maximum stress of 87.5 MPa and a safety factor of 2.83, ensuring its structural integrity. The hydraulic system, employing a double-acting cylinder operating at 10 bar, requires a motor power of 4.09 kW and achieves a fluid flow rate of 235.5 L/min. Cost analysis revealed a 30.44% reduction in manufacturing costs compared to similar commercial machines, totaling IDR 16.7 million. These findings demonstrate the efficiency, safety, and economic viability of the mixer, offering a promising solution for glycerin waste utilization in the cement industry.
Solar Powered Street Lighting in Rural Areas: A Value-Use Analysis of Green Technology Axiology
This study aims to analyze the utility value and axiological implications of the application of green technology, namely Solar Powered Street Lighting (PSL), in Duri Village, Slahung District, Ponorogo Regency. The main problem in the village is the lack of a public street lighting system due to the limited PLN electricity network on the connecting roads between villages. Through an axiological review, this solar power plant technology is analyzed not only from a technical aspect, but also from its beneficial value for community life. The research method includes field studies, planning, implementation of independent Public Street Lighting technology equipped with automatic sensors, implementation testing, and mentoring. The results of the implementation of one Public Street Lighting unit using solar electricity using Smart Bright Solar cell technology with 4000 lm lighting show that this technology provides an independent lighting solution for the general public, improves security, and supports environmental sustainability. The application of solar power plant on Public Street Lighting in rural areas realizes the axiological value of science as a means to improve the quality of life and create energy independence in remote areas.
An Epistemological Approach to Explainable Automated Assessment of Open Concept Map Propositions Using SHAP
Concept mapping is widely recognized as an effective method for supporting meaningful learning and critical thinking because it allows teachers to assess students’ underlying knowledge structures. However, evaluating concept maps and providing feedback remain challenging, as these processes are time-consuming, increase teachers’ workload, and can reduce instructional efficiency. To address this issue, this study applies Transformer-based architectures, which rely on large-scale pre-training and task-specific fine-tuning, to develop an automated assessment system for concept maps. In addition, Explainable Artificial Intelligence (XAI) is integrated through the SHAP (SHapley Additive exPlanations) framework to generate interpretable explanations of the model’s scoring decisions. Using Transformer models such as BERT and DeBERTa, SHAP values are computed at the token level to show how individual words within each proposition contribute to the final score. The results indicate that tokens with positive SHAP values increase scores in line with correct rubric indicators, whereas negative values reduce them. Tokens that consistently show positive contributions in high-scoring outputs reflect stable and faithful model reasoning. Overall, the findings demonstrate that combining Transformer-based assessment with SHAP explanations improves epistemic transparency by aligning the model’s internal reasoning with expert evaluation criteria, thereby supporting more reliable, interpretable, and trustworthy automated feedback in concept mapping-based learning.
The Application of Machine Learning in Liver Disease Diagnosis: Analysis of Algorithm Performance and Axiological Implications
Liver disease remains a significant global health challenge, requiring accurate and timely diagnosis to improve patient outcomes and reduce healthcare costs. This study investigates the application of four machine learning classification algorithms—Decision Tree, Random Forest, Naïve Bayes, and K-Nearest Neighbors (KNN)—to predict the presence of liver disease using a dataset sourced from Kaggle. These algorithms were evaluated based on performance metrics such as accuracy, precision, recall, and F1 score. Both Decision Tree and Random Forest achieved the highest accuracy rate of 72.41%, demonstrating their robustness in classifying liver disease cases. However, these models showed some limitations in identifying patients without liver disease. Naïve Bayes, with an accuracy of 60.34%, exhibited an impressive recall rate of 96.97%, indicating its potential in detecting liver disease cases, though at the cost of lower precision. KNN, with an accuracy of 70.69%, proved to be a competitive option in the classification task. Beyond technical performance, the study also explores the ethical and axiological implications of using machine learning in healthcare, emphasizing the importance of fairness, transparency, and human oversight. The research highlights the need for responsible deployment of machine learning technologies, ensuring they are aligned with ethical standards to avoid biases and enhance healthcare outcomes. This study demonstrates that machine learning can significantly support liver disease diagnosis, though it must be integrated with a comprehensive ethical framework to ensure equitable and transparent decision-making in clinical practice.