International Conference on Engineering, Construction, Renewable Energy, and Advanced Materials

An Innovative Method for Developing Sustainable Road Embankments with Lightweight Concrete Containing Palm Cell Ash

Samsunan — 2025-07-19

The use of industrial waste as an alternative material in construction is a strategic effort to promote sustainable development. This study examines the effect of the compressive strength of light concrete due to the partial replacement of cement with Palm Oil Fuel Ash (POFA) in the mixture, for environmentally friendly road construction The concrete was designed to have a specific density of 0.8 g/cm³, with POFA replacing cement at levels of 5%, 10%, 15%, and 20%, alongside a control mix without POFA. Mechanical tests, particularly compressive strength assessments, were conducted at 7 and 28 days. The findings revealed that adding 5% and 10% POFA reduced the quality of lightweight concrete, while at 15% and 20%, an increase in compressive strength was observed. This improvement at higher POFA levels is attributed to more effective pozzolanic reactions within the mix. The lowest strength was recorded at the 10% POFA composition, with a compressive strength of 5.12 kg/cm², which still meets the requirements for lightweight concrete used in road embankments. Thus, incorporating POFA in concrete has the potential to enhance quality while reducing cement consumption, aligning with the principles of sustainable road construction.

The Importance of Implementing Lean Construction in Construction Projects in Indonesia

Nurlaelah — 2025-07-19

This paper explores the implementation of Lean Construction in the Indonesian construction industry, focusing on its impact on improving project efficiency, reducing waste, and optimizing resource utilization. Lean Construction, a methodology derived from Lean Manufacturing, emphasizes value creation by eliminating non-value-added activities and fostering collaboration among all stakeholders. This study employs a qualitative research approach by exploring various literature related to the implementation of lean construction, both in Indonesia and in other countries. The findings suggest that adopting Lean Construction in Indonesia could address critical challenges in the sector, such as delays, budget overruns, and inefficient resource management, contributing to the industry's competitiveness and growth. Finally, the paper discusses the potential benefits of integrating Lean Construction with other innovative technologies, such as Building Information Modeling (BIM), to further streamline construction processes and achieve higher levels of project success

Detecting Potential Vessel Loitering Behavior from Ship Trajectories Using a Hybrid Rule-Based and Neural Network Approach

Widyadi Setiawan — 2025-07-19

Vessel loitering behavior is one of the essential indicators in detecting suspicious maritime activities, such as illegal fishing, smuggling, and territorial waters violations. Loitering is characterized by slow movements and random changes in direction and lasts for an extended period. This research aims to automatically identify potential vessel loitering behavior based on trajectory data from the Automatic Identification System (AIS) with a hybrid approach that combines rule-based methods and neural network models. AIS data is collected from Udayana University Receiver Base Station within a specific period and consists of millions of ship position data. The initial process includes data cleansing, trajectory extraction, trajectory cleaning, and loitering feature extraction based on temporal and spatial parameters. A rule based approach is used to identify loitering candidates at the loitering extraction stage, which is used to label trajectory data as loitering or not. The labeled data is then trained to automatically train a neural network-based classification model to recognize loitering patterns. The model evaluation results showed excellent performance, with accuracy, precision, recall, and F1-score on the test data.

Comparison of You Only Look Once (YOLO) and Single Shot Multibox Detector (SSD) Methods for Object Detection Using OpenCV

Mohamad Rafi Adidama — 2025-07-19

Object detection is a crucial field in image processing and computer vision, playing a vital role in applications such as security, industrial automation, human-computer interaction, and autonomous vehicles. As the demand grows for fast, accurate, and real-time systems, deep learning-based object detection methods have become a primary choice. This study aims to evaluate and compare the performance of two popular methods, You Only Look Once (YOLO) and Single Shot MultiBox Detector (SSD), using OpenCV as the development platform. The evaluation focuses on key parameters, including detection accuracy, processing speed, resource efficiency, and real-time applicability. The COCO dataset was used for testing, as it offers diverse object categories with variations in lighting conditions, background, and object sizes. Pre-trained YOLOv3 and SSD models were implemented using Python. The results indicate that YOLO achieves higher processing speed, with an average frame rate of up to 45 fps, making it ideal for fast-response applications such as surveillance systems. Conversely, SSD demonstrates better accuracy in detecting small objects, although its processing speed is slightly lower than YOLO. Further analysis reveals that YOLO relies heavily on GPU for optimizing processing speed, whereas SSD depends more on CPU, making it suitable for devices with limited resources. This study provides valuable insights for developers and researchers in selecting the most appropriate object detection method for specific needs, whether for real-time applications or scenarios requiring high accuracy. Understanding the strengths and limitations of each method enables optimized object detection technology for various future applications.

Performance Optimization of PAC and Activated Carbon in COD Reduction for Palm Oil Wastewater Treatment

Fakhri Nurul Firdaus — 2025-07-19

Palm oil industrial processing generates two types of waste: solid and liquid. Solid waste, such as empty fruit bunches, fibers, and shells, is commonly managed through designated disposal facilities. Meanwhile, liquid waste requires proper treatment before being discharged into the environment. One of the essential parameters in wastewater treatment analysis is Chemical Oxygen Demand (COD). This study aims to determine the optimal conditions for COD reduction using the Jar Test method by comparing two coagulants: Poly Aluminium Chloride (PAC) and Activated Carbon. In the treatment of palm oil mill wastewater using PAC, the optimal reagent concentration was found to be 80 ppm, achieving a COD reduction of 29.51%. For the adsorption process with a PAC-Activated Carbon mixture, the optimal activated carbon concentration was 4 g, resulting in a COD reduction of 48.79%. The findings of this study indicate that optimizing coagulant dosage and coagulation-adsorption conditions significantly enhances wastewater treatment efficiency in reducing COD levels.

Cassava Peel Waste Potential as Biobriquette Feedstock for Power Plant Co-Firing: A Review

Aisyah Rachma Hayati — 2025-07-19

The utilization of renewable energy has become a key strategy in supporting energy transition and reducing dependence on fossil fuels. One emerging approach is co-firing technology, which involves blending biomass fuel with coal in power plants. This study aims to review the potential of cassava peel waste as a raw material for biobriquette production for co-firing applications. Cassava peel, an abundant agro-industrial waste, contains cellulose and lignin, which enable it to be carbonized into charcoal and subsequently formed into biobriquettes. This study examines the potential of biobriquettes made from cassava peel charcoal with a focus on raw material availability, cost of energy, and environmental emission impacts. The review indicates that cassava peel charcoal biobriquettes have promising potential as an alternative fuel, although optimization is still needed in terms of densification, binder selection, and combustion efficiency. With proper processing, cassava peel waste can serve as a sustainable energy solution that supports the decarbonization program in the power generation sector.

The Effect of Gelatinization Time on The Characterization of Edible Films from Soybean Hull Waste

Aqil Pratama Nugraha — 2025-07-19

Soybean hull waste is waste from agroindustry, containing high cellulose. Soybean hulls can be utilized as edible film combined with starch. This study investigates the effect of gelatinization time on physicochemical properties of edible films produces from soybean hull waste. Soybean hulls combined with starch were processed into film-forming and subjected to varying gelatinization times (20, 30, 40, 50 and 60 minutes) by solvent casting method. The resulting films were evaluated thickness, water vapor transmission rate (WVTR), solubility, water contain and biodegradable rate. The result demonstrated that increasing gelatinization time significantly the reducing WVP, moisture contain, and higher biodegradable index. However, excessive gelatinization caused polymer degradation, negatively impacting thickness, and solubility. This study highlights the critical role of processing parameters, particularly gelatinization time, in optimizing the functional properties of edible films from soybean hull waste, offering a promising avenue for value-added utilization of agro-industrial residues in biodegradable packaging applications.

Optimization of gelatinization time of edible film from rice bran

Dani Riyanto — 2025-07-19

Rice bran has the potential to be used as edible film using the gelatinization process. The aim of this research is to optimize the gelatinization time in making rice bran edible film. The analytical method used is; analysis of solubility in water and water vapor permeability. The results showed that gelatinization time had a significant effect on the solubility of edible film. The weight of the film lost is expressed as the total weight of the film dissolved in water during immersion. The solubility percentage of edible film ranges from 65 – 79%. The results of the analysis of the various effects of treatment on the solubility level of edible film at 6 hours of immersion showed that the gelatinization treatment time of 50-80 minutes had a significant effect on the solubility percentage. Meanwhile, variations in gelatinization time of 90 minutes experienced a decrease in the solubility percentage. The highest water vapor transmission rate is found in edible film with a time variation of 50 minutes. The water vapor transmission rate increases with increasing gelatinization time. Physical test results for tensile strength 0.30 (N/mm2), elongation 13.77%, elastic modulus 4.07 (N/mm2].

Carbon Nanotube Yarn for Lightweight Composite Structure – A Potential for Reducing Carbon Emissions in Aircraft

Redha Akbar Ramadhan — 2025-07-19

Carbon nanotube yarns (CNTYs) have emerged as a promising class of materials with extraordinary strength-to-weight ratios, making them strong candidates for next-generation lightweight structural applications. In aerospace, reducing structural mass is critical to improving fuel efficiency and minimizing carbon emissions. This report explores the structural characteristics of CNTYs, their potential advantages over conventional carbon fibers, and their applicability in high-performance composites aimed at sustainability goals. Key challenges to widespread adoption are also discussed, including fabrication, interface mechanics, and standardization

Prediction of Gas Turbine Performance Utilizing Hybrid LSTM-RFE Models and Bayesian Optimization for Hyperparameter Tuning

Tri Handoyo — 2025-07-19

Accurate prediction of gas turbine performance is essential for optimizing reliability and efficient maintenance scheduling in oil & gas industry. This research introduces a novel hybrid framework that integrates Long Short-Term Memory (LSTM) networks with Recursive Feature Elimination (RFE) for feature selection, enhanced by Bayesian Optimization for hyperparameter tuning. Results revealed that the approach effectively reduces input dimensionality, focuses learning on the most informative variables, and automates parameter tuning for optimal model configuration. The LSTM model, trained on a high-resolution operational dataset, achieved exceptional predictive performance with a Mean Squared Error of 0.0000, Mean Absolute Error of 0.0023, and an R² score of 0.9980. Visualization of actual vs. predicted engine power confirms the model’s robustness in capturing both steady-state and transient behaviors. These findings underscore the potential of hybrid deep learning approaches to improve predictive analytics for gas turbines, providing a scalable solution for intelligent monitoring and decision-making in energy systems

Experimental Study on Single Phase Immersion Cooling for Cylindrical Lithium-Ion Batteries

Dhanang Sulistio Aji — 2025-07-19

Effective thermal management is essential for maintaining the safety and operational efficiency of lithium-ion batteries, particularly in electric vehicle (EV) applications. This study investigates the thermal performance of a single-phase immersion cooling system utilizing a hydrofluoroether (HFE)-based dielectric fluid, in comparison with natural convection cooling, for 18650-type lithium iron phosphate (LiFePO4) cylindrical batteries. Specifically, the effectiveness of the HFE-7100 fluid in regulating battery temperature was evaluated. Experimental findings indicate that at a discharge rate of 3C, the maximum average surface temperature reached 40.1 °C under natural cooling, while immersion cooling limited it to 31.5 °C. This represents a 21.45% reduction in surface temperature achieved through immersion cooling. These results demonstrate that immersion cooling not only significantly reduces battery temperatures but also promotes more uniform thermal distribution, highlighting its potential as an efficient approach for battery thermal management systems

Design and Construction of Transmission of Dry and Wet Spice Grinding Machine with Capacity of 20kg/Hour

Muhammad Riyaldi Saputra — 2025-07-19

The spice grinding process, whether manual or automatic, affects the quality and efficiency of production. This study aims to design a transmission system used in a wet and dry spice grinding machine with a capacity of 20 kg/hour and to analyze the efficiency applied to the wet and dry spice grinding machine. The design process in this study includes several stages including transmission design, blade selection and the creation of a sturdy frame. The transmission design was chosen belt and pulley because it allows slippage. While for the design of the knife, the Burr grinder was chosen which was a dry spice grinder equipped with a serrated knife, which was designed to grind spices efficiently to achieve optimal consistency. The results shows the calculations carried out on the transmission on the dry spice grinder, the specifications needed are an electric motor of 1.17 HP with a shaft strength of 0.0872 Kw and producing a torque of 4.84 Nm, then the transmission can grind an average of 17.34 Kg / hour. The shrinkage that occurs in the grinding process on all indicators is no more than 50%, which means a high level of efficiency so that this transmission can be relied on to do grinding work. The transmission used worked well during testing.

Power Generation Prediction of a Reheat-Regenerative Combined Cycle Steam Turbine Using an Artificial Neural Network

M. Farhan Ramadhany — 2025-07-19

Enhancing steam turbine efficiency in load management is challenging due to operational non-linearity and complexity. This study develops an Artificial Neural Network (ANN)-based prediction model for electric power generation in reheat-regenerative combined cycle steam turbines. Data preprocessing involved missing value removal and outlier detection using K-Means Clustering and the Grubbs Test, followed by Principal Component Analysis for dimensionality reduction. From 50 initial features, 13 key features were selected, explaining 95% of variance. The ANN model employed Bayesian Regularization, tangents sigmoid activation, and five hidden layers (22, 18, 14, 10, 6 nodes). Performance evaluation yielded an MSE of 0.00177, RMSE of 0.04203, and R² of 0.9985, demonstrating high accuracy. This study supports operational planning at the Banjarsari coal power plant, offering a neural network-based predictive approach to improve energy generation efficiency sustainably.

Comparative Analysis of Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) Models for Gas Turbine Performance Prediction

Abdul Rohman Rusdan Arif — 2025-07-19

Gas turbines are essential for offshore operations in the oil and gas industry due to their lightweight structure and high efficiency. Conventional maintenance relying on parameter monitoring and engine washing often causes unplanned downtime and suboptimal recovery. This study develops gas turbine performance prediction models using Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) deep learning approaches. Historical operational data were preprocessed through cleaning, normalization, and feature selection using Random Forest and LASSO. The LSTM model achieved an RMSE of 3.96 and an R² of 0.9991, while the GRU model achieved an RMSE of 4.58 and an R² of 0.9988. Comparative analysis showed that LSTM slightly outperformed GRU in accuracy, although GRU converged faster. These findings demonstrate the potential of integrating deep learning methods into predictive maintenance frameworks to enhance gas turbine reliability and efficiency

Analysis of Raw Material Inventory Control Using the Fuzzy EOQ Method at CV. XYZ

Muammar Khadafi — 2025-07-19

Inventory planning and control are crucial for CV XYZ, a furniture industry in East Jakarta, due to demand fluctuations and raw material limitations. Over the past 12 months, a stockout of 60 mahogany logs resulted in potential losses of Rp 14,000,000 – Rp 40,000,000. This study compares the company's policy, EOQ, and fuzzy EOQ methods in inventory management. The results show that the EOQ method reduces inventory costs by 60.8% with an optimal order quantity of 255 logs, while fuzzy EOQ is more efficient, achieving a 64.3% cost reduction with an optimal order of 233 logs. With a lower ordering frequency, fuzzy EOQ is more effective in minimizing the risk of overstock, making it the best method for optimizing inventory and cost efficiency.

The Effects of Relationship Quality, Contract Governance, and Clinical Appropriateness on the Occupational Health Unit Outsourcing Performance

Syafira Andyah Putri — 2025-07-19

Outsourcing occupational health services enables companies to focus on their core competence while ensuring regulatory compliance and workforce well-being. However, inefficient contract governance, poor relationship quality, and inadequate clinical standards often lead to service disruptions, financial losses, and reputational risks—undermining long-term sustainability. This study examines how contractual governance (CG), relationship quality (RQ), and clinical appropriateness (CA) influence occupational health unit outsourcing performance (OHUOP) in Indonesia’s industries such as mining, oil & gas, manufacturing. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on survey data from 84 outsourcing contracts, we find that all three factors significantly enhance OHUOP, with RQ acting as a key mediator.

Improving Service Quality Towards Customer Satisfaction at Coffee Luvium using The Servqual Method

Ahmad Fauzan — 2025-07-19

Increased consumption of coffee along with consumptive nature and changes in people's lifestyle. Coffee is one of the most consumed drinks in Indonesia. Coffee Luvium is one of the businesses engaged in FNB. Based on the results of the study using the servqual method conducted on Coffee Luvium, found 5 priority factors that affect the level of customer satisfaction. The five factors are: 1) Speed of Coffee Luvium service systems in serving customers, 2) good speed and responsiveness from the management of Coffee Luvium in responding to customer complaints, 3) timeliness in the presentation of food and drinks to customers, 4) customer safety and comfort while in Coffee Luvium, 5) Speed of Management in providing solutions if there are complaints from customers. With gap values (gap) -1,16, -1.74, 1.78, -1,79, and -1.57. In this study discussed improvement recommendations to increase customer satisfaction Coffee Luvium.

Performance Measurement Analysis using The Human Resources Scorecard Method

Mutmainah — 2025-07-19

Due to the fact that the performance of employees is one of the metrics that determines the success of a company, it is imperative that the management of human resources receives the serious attention it deserves. Up until this point, the performance measurement that has been carried out by PT. XYZ has solely evaluated the employee's soft skills, and it is subjective. As a result, there is a requirement for a comprehensive or comprehensive measurement of human resource performance, such as the Human Resources Scorecard (HRSC). The Human Resource Service Center (HRSC) is evaluated based on four distinct perspectives: financial, customer, internal business processes, and growth and learning. The key performance indicators (KPI) from each of these views will be used to measure the impact of each perspective. AHP (Analytical Hierarchy Process) and OMAX (Objective Matrix) are utilized in the process of weighting measurements, and the evaluation processes are carried out in comparison to criteria that are associated with the performance of the firm.

The RCM method is used to identify critical components and design maintenance strategies for the head truck

N Nelfiyanti — 2025-07-19

As a private company engaged in the supply and maintenance of port equipment, PT XYZ faces operational challenges due to the high downtime of heavy equipment used. Based on 2019 data, Head Truck is the tool with the largest total disruption hours of 7,135 hours or 72% of the total downtime of the three main types of equipment, followed by RTG of 830 hours (8%) and QCC of 1,970 hours (20%). The high downtime has a direct impact on reducing operational efficiency and losses for the company. In order to improve the reliability of the Head Truck engine, an analysis was conducted using the Reliability Centered Maintenance (RCM) method which includes system identification, function and failure analysis, to the application of Failure Mode and Effect Analysis (FMEA) to find critical components and recommendations for optimal maintenance actions. The results of MTTF (Mean Time To Failure) and MTTR (Mean Time To Repair) calculations show that the crankshaft Assy component has the fastest repair time, which is an average of 2.16 hours, while the piston Assy component requires the longest repair time of around 5.75 hours. With this data, a periodic maintenance schedule is created that is adjusted to the frequency of damage and recovery time of each component, so that it can help minimize the risk of downtime and increase the operational effectiveness of the Head Truck engine.

Implementation of OEE as a Strategy to Increase Kanzaki Shaving Machine Productivity in the Context of the Industrial Revolution 4.0

Andry Setiawan — 2025-07-19

This study aims to measure and analyze Overall Equipment Effectiveness (OEE) as a strategy to improve productivity on the Shaving Kanzaki Machine in a manufacturing company within the context of Industry 4.0. Based on the calculation results, the OEE values for January and February 2025 were 24.5% and 23.9%, respectively, which are far below the world-class OEE standard of 85%. The availability component was recorded at 33.3%, performance ranged between 74-76%, and quality reached 97%. These results indicate that the low availability is the dominant factor contributing to the poor OEE, followed by suboptimal performance, although the quality aspect is relatively good.

As a solution, the study proposes the implementation of improvements based on Total Productive Maintenance (TPM) and the integration of Industry 4.0 technologies, such as the Internet of Things (IoT), big data analytics, AI-based predictive maintenance, and machine vision systems for product quality control. Additionally, enhancing operator competencies through digital data-driven training and the implementation of a real-time OEE monitoring dashboard are recommended to facilitate effective machine performance monitoring. Previous research supports that the combination of TPM and Industry 4.0 technologies is effective in improving OEE and productivity in the manufacturing sector. With the implementation of this strategy, the OEE of the shaving machine is expected to increase significantly, thereby enhancing both productivity and the company's competitive advantage.

Climate Adaptation In Tambi Traditional Houses, Central Sulawesi, Indonesia

Chalisha Dhiya Ramadhani — 2025-07-19

Tambi Traditional House is a traditional house located in Central Sulawesi. This traditional house is a reflection of architectural work that is full of tradition and meaning and contains local wisdom and is a solution to local climate problems. The form of the building and the materials used are two aspects that can be used to identify and analyze climate adaptation in the Tambi traditional house, Central Sulawesi. This study aims to identify, describe and reveal the climate adaptation applied by the Tambi traditional house. The image data taken in this article is secondary data, from scientific journal literature. The main materials used include bonati wood, bamboo, and ijuk, each of which has a specific function in the structure and design of the house. The pillars in the Tambi traditional house use wood because they have high compressive and tensile strength. In addition, because of its resistance to pests and rot, this material is also used as the main frame. Bamboo in the Tambi traditional house is used as a wall element because it is porous so it can support air circulation in the house. Meanwhile, ijuk is used as a roof because of its good water resistance and thermal insulation properties. This study found that the shape of the stage and the steep roof angle are solutions to the local climate. In addition, the local materials used are not only environmentally friendly but also reflect harmony with nature and resources. The results of this study are expected to increase insight into traditional architecture, especially the Tambi traditional house, as an architectural heritage that responds to the climate in its design and materials.

Study on the Application of ETFE Material on Building Envelopes in Relation to Indoor Thermal and Visual Comfort Case Study: South Quarter Dome Building, Jakarta

Reinadini Prawadya — 2025-07-19

For the past two decades, energy issues have been in the spotlight in building construction and design. Environmental damage such as global warming, climate change and energy crisis are challenges that need to be considered by the entire community. These problems greatly affect our lives in the future, air pollution, increasing city temperatures (urban heat island), and declining environmental quality affect human comfort and health. This study discusses the effectiveness of ETFE (Ethylene Tetrafluoroethylene) material on the South Quarter Dome building, South Jakarta, in improving thermal and visual comfort through temperature insulation and light transmission. This study aims to determine the performance or effectiveness of using ETFE material on building facades to improve the comfort of indoor spaces. The method used is mixed methods, which combines two research techniques with research variables, namely air temperature (^oC) on thermal comfort and lighting intensity (lux) on visual comfort. The results of this study indicate that the magnitude of the light transmission measurement value on the visual comfort of the South Quarter Dome is 1-95% and the magnitude of the decrease in outside to inside temperature is 0.2-1.3 ^oC. This shows that ETFE material is able to control natural lighting well, which can minimize the use of electricity for artificial lighting and has good ability to regulate temperature, so it can create thermal comfort for its occupants.

Architectural Review of Islamic Civilization in the Arabian Peninsula, Persia, and Africa Case Studies: Umayyad Mosque, Sheikh Lotfollah Mosque, Sankore Mosque

Hana Halimah — 2025-07-19

Islamic architecture developed alongside the widespread expansion of Islam, integrating with each region’s geographic conditions and cultural heritage. This research applies a qualitative descriptive approach with literature review as the primary method. The study focuses on identifying architectural characteristics in the Arabian Peninsula, Persia, and Africa. In Arabia, early mosque design reflects simplicity and a deep connection with nature. Persian architecture is marked by rich decorative elements like domes and iwans, highlighting spiritual expression. In Africa, Islamic buildings reveal strong adaptation to desert climates while retaining symbolic religious value. The findings emphasize that Islamic architecture is not merely a structural form, but a representation of tawhid principles, communal unity, and distinctive cultural identities across different regions.

Quantum Iris Classifier: A Pennylane-Based Approach

Widi Hastomo — 2025-07-19

The advancement of quantum computing has opened new opportunities in data processing and machine learning, particularly through the implementation of efficient variational quantum algorithms. This study explores the implementation of a Quantum Neural Network (QNN) using the Pennylane framework to perform multi-class classification on the classical Iris dataset. By designing a quantum ansatz composed of rotation parameters and CNOT entanglement gates, the model is trained using the Gradient Descent algorithm to minimize a loss function based on softmax cross-entropy. The training process is conducted over 200 epochs, with accuracy and loss evaluations recorded every 10 iterations. Experimental results show that this approach can achieve a maximum accuracy of 96.67% in certain iterations and maintain stable performance above 93% throughout most epochs. This study highlights the potential of hybrid classical-quantum models as a competitive alternative to traditional learning methods, paving the way for broader applications of quantum technologies in small- to medium-scale data classification

Maggot Sales Application On Larva Go Using Search Engine Optimization (SEO)

Khalid Jundullah — 2025-07-19

Larva Go is a maggot-based waste management business derived from the larvae of the Black Soldier Fly (Hermetia illucens). These maggots produce highly nutritious larvae as animal feed and residue in the form of quality organic fertilizer in organic waste management. However, the business faces the challenges of a manual sales system through WhatsApp, limited marketing, and error-prone manual recording. To overcome these problems, research was conducted using the Waterfall software development model, and Search Engine Optimization (SEO) optimization. The goal is to expand marketing reach, automate the sales process, and manage customer data. The application is equipped with features such as product information, ordering, payment through Midtrans, and special delivery for the Tegal Regency area. The results showed that the maggot sales application was successfully developed and has been hosted so that it can be accessed online. Testing was conducted by twenty users, the results of which 93% showed that the application functioned well and provided an easy user experience, from registration, ordering, to automatically integrated payments. In addition, Larva Go search optimization through search engine optimization with on-page methods has been implemented and successfully found in search engines, at the top rank

Analysis of High Blow-By Pressure Issues in the Komatsu HD 785-7 Dump Truck

Indra Gunawan — 2025-07-19

Dump trucks play a key role in transporting heavy materials in sectors like construction and mining. The HD 785-7 dump truck (engine serial number 509396) experienced blow-by pressure of 6.5 kPa, exceeding the normal range of 2.94 kPa – 5.88 kPa. This issue arises when combustion gases leak past the piston rings into the crankcase, often due to worn rings or cylinder head damage. High blow-by pressure results in reduced engine performance, increased oil consumption, and internal component damage. The study aims to identify the cause of this issue, propose solutions, and suggest preventive measures. The analysis revealed that gravel blockage in the cooling nozzle area caused insufficient lubrication and cooling, leading to piston cracking and cylinder wear. Regular maintenance and thorough inspection of the lubrication and cooling systems are essential to prevent such failures.

Design of a Removal Tool for Air Dryer Filters on Scania P410 Using the 7UP++ Method

Muhammad Rizki — 2025-07-19

This study aims to design and evaluate the effectiveness of a specialized tool to facilitate the removal process of the air dryer filter on Scania P410 units, particularly in cases where the locking nut is detached. Common issues such as difficulty in filter removal, risk of thread damage, and potential harm to surrounding components are the main focus of this research. The custom-designed tool provides optimal grip without damaging adjacent parts, thereby improving maintenance efficiency and reducing the risk of component failure. Testing results show that the use of this tool can significantly reduce filter removal time from 30 minutes to just 5 minutes, representing an efficiency improvement of 83.3%. Therefore, the tool is proven to be effective in supporting maintenance processes, enhancing technician safety, and minimizing vehicle downtime. This study recommends the widespread adoption of the specialized tool and technician training to ensure safe and efficient air dryer filter maintenance.

Failure Analysis of Fan Motor in Komatsu Bulldozer D155-6 Unit

Rasma — 2025-07-19

The cooling system is one of the most critical components in heavy equipment such as the Komatsu Bulldozer D155-6. Approximately 40% of engine failures are caused by issues within the cooling system, highlighting its importance in maintaining engine temperature and preventing overheating. This study focuses on the failure analysis of the fan motor, a key component in the cooling system. The fan motor plays a vital role in regulating engine temperature by ensuring optimal airflow through the radiator. Through field inspection and diagnostic analysis, it was found that engine overheating was primarily caused by abnormal fan speed, which resulted in inadequate cooling. The root cause of this issue was identified as a malfunction in the fan motor. This paper presents the steps taken to diagnose the problem, the components that were replaced, and recommendations for future preventive maintenance. These findings aim to enhance equipment reliability and operational efficiency in heavy-duty applications.

Effects Of Seedling Age On The Growth And Yield Of white Pakchoy Plants In The Wick Hydroponics System

Arif Akbar — 2025-07-19

This study aims to determine the effect of sowing age on the growth and yield of white pakchoy (Brassica rapa L.) using a wick hydroponic system. The research was conducted at the Faculty of Agriculture, Universitas Muhammadiyah Jakarta, employing a Completely Randomized Design (CRD) with five sowing age treatments (1, 3, 5, 7, and 9 days after sowing/DAS), each replicated five times. Observed parameters included plant height, number of leaves, leaf size, root length, fresh weight, and consumption weight. Results showed that sowing at 9 DAS produced the best growth performance, with a plant height of 19.87 cm, 8.73 leaves, fresh weight of 27.73 g, and consumption weight of 24.93 g. These findings suggest that sowing white pakchoy at 9 DAS optimizes growth and yield in wick hydroponic systems, particularly for the Panda Farm variety.

Growth and Morphological Characteristics of Six Romaine Lettuce Varieties in Lowland under Paranet Shade

Zahra Zulita Rahma — 2025-07-19

Romaine lettuce is a type of introduced vegetable gaining popularity in Indonesia. There are not many romaine lettuce varieties that are suitable to be grown in the lowlands to fulfil the demand. The study aimed to determine the growth and morphological characteristics of six romaine lettuce varieties grown in the lowland area. This study was conducted from February to April 2024 on a house rooftop in Bojongsari, Depok, West Java. The study used a randomized complete block design (RCBD) with treatment of various varieties of romaine lettuce consisting of six different varieties: Green Romaine, Red Romaine, Parris Island, Dacosta, Maximus, and Tiberius. The results showed that the Tiberius variety had the highest growth variables (crop height, number of leaves, leaf length, leaf width, gross weight, and consumption weight). All six varieties had the diversity of head shape, leaf color, leaf shape, leaf tip shape, and leaf attitude.

COMPETITIVENESS OF MAJOR PRODUCING COUNTRIES IN WORLD COFFEE TRADE

Lola Rahmadona — 2025-07-19

This study aims to analyze the competitiveness and trade specialization of coffee exports from the world's five major producing countries, namely Brazil, Vietnam, Colombia, Indonesia, and Ethiopia, during the period 2004–2023. Secondary data used included five HS codes for coffee commodities (0901, 090111, 090112, 090121, and 090122) collected from Trademap and FAOSTAT. The analytical methods used included Revealed Comparative Advantage (RCA) to measure competitiveness and the Trade Specialization Index (TSI) to identify the level of trade specialization. The results showed that coffee exports with HS codes 0901 and HS 090111 were the most competitive product groups among the five producing countries. Ethiopia had the highest and most consistent RCA values, while Brazil and Vietnam showed a downward trend in competitiveness. In contrast, Colombia showed a significant increase in competitiveness in roasted coffee products. Meanwhile, coffee exports under HS codes 090112, HS 090121 and HS 090122 generally do not show strong competitiveness. In terms of ISP, most countries have reached export maturity levels for HS 0901 and HS 090111, indicating their position as net exporters and have achieved the set production standards. However, fluctuations in ISP values in some countries indicate changes in export patterns and competitive dynamics in the world market.