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This study conceptually examines a self-supervised multi-scale fusion framework designed to enhance accuracy and computational efficiency in medical image segmentation, a domain where data scarcity and annotation cost remain major challenges. Traditional supervised approaches are constrained by their reliance on extensive labeled datasets, limiting applicability in real-world clinical environments. Self-supervised learning (SSL) mitigates this issue by extracting supervisory signals directly from unlabeled data, enabling the model to learn rich feature representations without human annotation. Simultaneously, multi-scale fusion architectures integrate global contextual information with fine-grained local features, supporting robust segmentation across varying anatomical structures and image resolutions. Through a qualitative methodology involving library research and content analysis, this study synthesizes state-of-the-art SSL-driven segmentation techniques and highlights how adaptive multi-scale fusion mechanisms address limitations of existing convolutional and transformer-based architectures. The analysis indicates that combining SSL and multi-scale strategies leads to more generalizable, scalable, and computationally efficient segmentation pipelines suitable for diverse medical imaging modalities. The proposed framework represents a promising direction for developing next-generation diagnostic tools capable of handling sparse labels, complex textures, and real-time deployment constraints.

This study aims to explore the institutional governance and collaboration mechanisms at Indonesia's entry points, emphasising both formal arrangements, such as Memoranda of Understanding, and informal communication channels that facilitate daily operations among Immigration, Customs, Port Authorities, Law Enforcement, and Health Agencies. The research employed qualitative methods, including interviews, observations, and document analysis, grounded in Policy Network theory, to analyse the dynamics of institutional collaboration at entry points. The findings highlight that border oversight effectiveness hinges on inter-agency synergy quality, trust, and the ability to overcome technical and procedural barriers, whilst significant challenges include technological disparity, particularly incompatible data platforms hampering real-time information sharing, and silo mentalities driven by security concerns that impede operational harmonisation, resulting in delays and inefficiencies. Trust mechanisms such as informal communication groups, regular meetings, and leadership support significantly improve coordination and operational performance. The study concludes that sustainable and adaptive governance models characterised by mutual trust, effective communication, and technological integration are essential for enhancing border security and facilitating legal movement. The research underscores the importance of integrating technological systems to ensure interoperability, developing clear cross-agency SOPs, and fostering a collaborative culture that prioritises shared goals over organisational ego. Strengthening institutional collaboration at border crossings will bolster Indonesia's national security, economic growth, and international reputation, and contribute to resilient, efficient border management systems capable of addressing contemporary threats.

Dynamic programming (DP) is a foundational technique for solving multistage optimization problems; however, its classical formulation often incurs a cubic time complexity, rendering it impractical for large-scale real-world applications. This study proposes an accelerated dynamic programming framework that leverages quadrilateral inequality and convex monotonicity theory to significantly reduce computational overhead. By formally establishing the structural conditions under which DP decision boundaries exhibit monotone behavior, the proposed method eliminates redundant state transitions and maintains a sequence of admissible decisions through an efficient stack-based mechanism. The resulting algorithm achieves a worst-case complexity of O(n2) and can be further optimized to O(n) when convex monotonicity holds, representing a substantial improvement over traditional O (n3) techniques. Experimental validation using the classical stone-merging problem demonstrates that the accelerated method executes more than 60 times faster than the standard approach for large inputs, while maintaining identical optimal results. These findings confirm that embedding geometric regularities into DP formulations not only enhances performance but also broadens the applicability of dynamic programming to computation-intensive optimization tasks. This research contributes a mathematically grounded, scalability-oriented solution for accelerating dynamic programming, with implications for logistics, production planning, data segmentation, and other large-scale decision systems.

This study aims to examine the implementation of bureaucratic reform at the Immigration Document Section of Ngurah Rai Immigration Office, focusing on digital transformation through the M-Paspor application to realise a dynamic immigration management system. The research employed qualitative analysis to evaluate service efficiency, transparency, accountability, and staff capacity in the context of digital innovation aligned with Dynamic Governance principles. The findings reveal that digitalisation has significantly enhanced service efficiency through automated procedures, reduced physical queues, and improved transparency, whilst facilitating a shift from manual tasks to core verification and problem-solving activities, though challenges persist regarding human resources capacity and organisational culture, as staff exhibit rule-bound mindsets and defensive communication styles when addressing service delays, thereby undermining public trust and satisfaction. The study concludes that technology alone is insufficient to achieve truly responsive and citizen-centric services, as institutional culture and personnel mindset require continuous strengthening through soft skills training, ethical enforcement, and cultivation of service-oriented, empathetic work culture. Holistic reform approaches that combine technological innovation with human resource development and cultural change are essential for building effective, adaptive, and transparent immigration management systems. The integration of digital systems complemented by professional human resources can foster seamless, efficient, and trustworthy immigration services aligned with good governance principles, whilst sustainable improvements depend on balancing technological advances with organisational culture development and staff professionalism.

The primary purpose of this activity is to enhance the capabilities of micro, small, and medium enterprises (UMKM) in managing wet cake production in a more hygienic and efficient way in order to generate products with higher market value. The skill development emphasizes technical improvements in the production process by prioritizing cleanliness, food safety, and consistent quality, as well as increasing efficiency in the utilization of raw materials and labor. This activity was implemented for UMKM operating under Dynala Food in Gentengan Hamlet, Padang Village, Singojuruh District, Banyuwangi. In addition to production aspects, the program also aims to strengthen marketing strategies at both local and digital levels, enabling tofu and wet cake products to be more easily accessed by consumers. The implementation was conducted through door-to-door visits and direct field observations. The program stages included socialization, hands-on training, technology application, mentoring, evaluation, and achievement of program objectives. Focus Group Discussions (FGDs) were conducted to identify challenges, formulate concrete action plans, and support the adoption of technology and digitalization in business development.

Human resource development is the process of preparing individuals to take on higher or different responsibilities within an organization, including enhancing intellectual abilities to support efficient task performance. This study aims to determine the extent to which human resource development contributes to improved employee performance at the East Lombok Regency Health Office. The qualitative, descriptive approach involved eight informants, consisting of officials familiar with the implementation of human resource development and staff who had participated in the program. The results indicate that education and training conducted by the East Lombok Regency Health Office have supported improved employee performance, as evidenced by more structured task implementation, public health monitoring surveys, and a decrease in maternal and infant mortality rates. However, in terms of human resource management, there are still shortcomings, with an average of 28 health workers per health facility, both civil servants and non-civil servants, reflecting an imbalance in workforce needs. Furthermore, the implementation of human resource development is supported by leadership commitment, inter-agency collaboration, and budget support from the provincial and central governments. However, it is hampered by limited qualified personnel, frequent policy changes, and the impact of natural disasters.

The rolling process is a material forming method that is greatly influenced by the roll rotation speed parameter. Inappropriate rotation variations can cause various defects such as waves, tears, thickness irregularities, and ovalization. This review aims to compare the effect of variations in the roll machine rotation speed on the quality of rolling results on various types of materials, including Al6061-O aluminum plate, rubber sheets, and hollow and pipe-shaped materials. The method used is a literature study by collecting and comparing data on roll speed, defects that appear, deformation results, and process efficiency from several relevant journals. The results of the analysis show that high rotation speeds increase productivity but also increase the risk of defects because the material does not have time to adapt to deformation. Conversely, low rotation speeds produce more stable shapes and minimize defects, but are less efficient for mass production. Each material has a different optimal rotation range, including 23–36 rpm for Al6061-O plate, 45–72 rpm for rubber sheet formation, 24.4 rpm for hollow and pipe rolling, and around 21 rpm for corrugated plate. Overall, this study confirms that rotational speed control is a critical factor in achieving a balance between deformation quality and machining efficiency.

The high-value horticulture sector has gained increasing attention in modern agricultural development, particularly in the cultivation of premium melon through greenhouse and fertigation systems. The Satria Tani Hanggawana Cooperative has initiated premium melon farming to enhance members’ income; however, investment decisions in high-value commodities require a comprehensive financial feasibility assessment to ensure business sustainability. This study aims to analyze the financial feasibility of premium melon farming by examining production costs, revenue, income, and financial efficiency indicators. Using a descriptive method with qualitative and quantitative approaches, the research was conducted through direct observation and interviews in two active greenhouses. The results show that the total production cost for one planting season reached Rp20,413,750, dominated by variable costs, reflecting the intensive input requirement to maintain product quality. The total revenue of Rp33,950,000 generated a net income of Rp13,536,250, indicating that the enterprise is financially profitable. The R/C Ratio of 1.67 confirms that the business operates efficiently, while the B/C Ratio of 0.67 indicates that net benefits remain below total costs due to reduced production caused by pest disturbances. The break-even analysis further shows that actual production far exceeded the minimum threshold required to avoid losses. Overall, the findings demonstrate that premium melon farming is financially viable, yet improvements in cost management, production monitoring, and greenhouse operational efficiency are essential to enhance profitability and long-term sustainability for the cooperative.

The integration of cloud computing and data security systems is vital for the operational success and competitiveness of fintech startups. Cloud computing enables these startups to scale quickly, manage resources efficiently, and reduce infrastructure costs, making it an indispensable tool for businesses in the rapidly evolving fintech sector. However, with the benefits come significant challenges, particularly in data protection and cybersecurity. As fintech services handle sensitive financial data, ensuring robust security measures such as encryption, access controls, and continuous monitoring is crucial to maintaining user trust. Furthermore, regulatory compliance, both local and global, adds complexity to the data protection strategies of fintech companies. This research explores the key factors that drive cloud adoption in fintech, the security challenges associated with cloud environments, and the strategies implemented by startups to address these challenges. Interviews with IT managers from Indonesian fintech startups reveal that while cloud computing offers scalability and cost-effectiveness, issues like compliance with local regulations and the protection of sensitive data remain major concerns. The research suggests that fintech startups should invest in both cloud infrastructure and advanced cybersecurity measures to protect their operations and customer data. Additionally, creating a comprehensive roadmap for regulatory compliance and fostering partnerships with cybersecurity firms will help mitigate risks and ensure long-term success. The findings highlight the importance of integrating cloud computing with effective security strategies to navigate the complex regulatory and security landscape of the fintech industry.

This study aims to analyze the effect of asset growth, capital structure, and asset structure on the profitability of PT Astra Graphia Tbk during the period 2016–2023. The research employs a quantitative approach with a causal research design using secondary data derived from the company’s quarterly financial statements. A total of 32 quarterly observations were selected through purposive sampling. Profitability is measured using Return on Equity (ROE), while data analysis is conducted using multiple linear regression. Prior to hypothesis testing, classical assumption tests including normality, multicollinearity, heteroskedasticity, and autocorrelation tests were performed to ensure the robustness of the regression model. The results indicate that asset growth, capital structure, and asset structure simultaneously have a significant effect on firm profitability. However, partially, only asset structure has a significant effect on profitability, while asset growth and capital structure show no significant influence. These findings suggest that efficient asset composition plays a more critical role in improving profitability than mere asset expansion or increased leverage. The managerial implication of this study highlights the importance of optimizing asset structure to enhance the firm’s ability to generate sustainable profits.

The disparity in the quality of rehabilitation services across regional work units presents a significant challenge to effective public management. This study aims to bridge the gap between problem diagnosis and policy prediction by proposing a hybrid, data-driven approach. We integrate K-Means Clustering to map the current state of service quality and Stochastic Simulation to predict the impact of strategic interventions. Using the 2024 Public Satisfaction Index (IKM) dataset from the National Narcotics Agency (BNN), the K-Means algorithm initially identified 26 work units (15.7%) in the "Red Zone" (critical performance), highlighting urgent areas for improvement. Next, a stochastic simulation modeling a "Directed Priority Intervention" scenario was run. The results predicted a significant structural shift in the distribution of service quality, characterized by an 80.8% decrease in critical units (down to 5 units) and a 71.8% increase in excellent performing units (up to 67 units). These findings validate that the integration of clustering and simulation provides a comprehensive framework for evidence-based decision-making, enabling policymakers to optimize resource allocation and efficiently accelerate national service standardization.

Hijaiyah letters have varying shapes, and some of them are very similar, often causing errors in the manual character recognition process. This study aims to classify Hijaiyah letters based on digital images using the Convolutional Neural Network (CNN) method. This method was used in this study with a dataset consisting of 28 letter classes and a total of 4,480 images obtained from various public sources and private data. All images underwent a preprocessing stage that included labeling, resizing, normalization, and augmentation, then were divided into three parts, namely training data, validation data, and test data with a ratio of 70:20:10. The training process was carried out using the Python programming language with the help of the TensorFlow and Keras libraries on the Google Colab platform. The test results showed that the CNN model achieved an accuracy of 97.10%, with an average precision, recall, and F1-score of 0.97, respectively. Classification errors only occurred in letters that had similar shapes, such as Syin and Sin. Based on these results, the CNN method proved to be effective, efficient, and accurate in recognizing Hijaiyah letter image patterns, so it can be used as a basis for developing classification models with higher accuracy in the future.  

This research examines the implementation of green building principles in the design of the Multipurpose Building at SMP–SMA Islam Hidayatullah Semarang, focusing on energy-efficient strategies and spatial comfort based on the GREENSHIP GBCI certification criteria. The study employs a qualitative descriptive method through interviews with the architect, analysis of architectural drawings, interpretation of interior design visualizations produced by Falana Studio, and literature review on sustainable building design. The findings indicate that the building consistently applies passive design strategies, including the optimization of natural lighting through large openings and a central void, the application of cross-ventilation on each floor, and the integration of façade vegetation that reduces surface temperature and improves microclimate performance. Material selection such as GRC panels, HPL, and modular plywood supports long-term durability, while the interior design demonstrates strong visual comfort and ergonomic quality through indirect lighting, neutral color schemes, and activity-based furniture layout. According to the GREENSHIP assessment categories, the building fulfills Energy Efficiency and Conservation (EEC), Indoor Health and Comfort (IHC), Material Resources and Cycle (MRC), and Appropriate Site Development (ASD) criteria. In conclusion, the Multipurpose Building successfully integrates green building principles as an effective approach to energy efficiency and the enhancement of the educational environment.

The increasing global energy demand drives the search for efficient and sustainable renewable energy solutions. Solar panels have become one of the most widely used technologies; however, their efficiency remains limited when installed in a static position. This research aims to analyze the performance of a single-axis auto tracking system on a 10WP solar panel integrated with the Internet of Things (IoT) for real-time monitoring, specifically in powering a portable powerbank. The research method employed was a quantitative experimental design with three testing scenarios: powerbank charging using an auto-tracking solar panel, a static solar panel, and conventional household electricity as a comparison. Charging data were collected via an IoT system integrated with the Blynk application in real-time. The results indicate that the auto-tracking system increased charging efficiency by around 10%, compared to only 6% with a static panel in one hour. This performance is nearly equal to household electricity charging, which reached approximately 10–11%. The study concludes that the single-axis IoT-based auto-tracking system significantly enhances the performance of small-scale solar panels and holds strong potential for portable energy solutions in remote areas.

This study aims to analyze inventory control of catfish seeds at ABC Company by comparing the conventional inventory method represented by the Economic Order Quantity (EOQ) approach and the Just In Time (JIT) system in order to improve cost efficiency. This research employed a descriptive quantitative approach using a case study design. Data were collected through direct observation, semi-structured interviews with company management, and documentation of inventory and cost records for the 2024 operational period. The analysis method involved calculating optimal order quantities, ordering frequency, delivery frequency, and total inventory costs using EOQ and JIT formulas, followed by a comparative cost efficiency analysis. The results show that the conventional method resulted in a total inventory cost of Rp 75,050,000 per year with high ordering frequency. In contrast, the implementation of the JIT system reduced inventory costs to Rp 18,762,500 per year, achieving a cost efficiency of 72%. These findings indicate that the JIT system is more cost-efficient than the conventional method; however, its implementation requires careful consideration of supplier capacity, logistics readiness, and biological risks associated with live inventory. This study contributes empirical evidence on the applicability of JIT in the aquaculture sector, which has different characteristics from manufacturing industries.

Plastic waste detection in indoor environments is an essential challenge in the development of intelligent cleaning systems and robotic automation. Small and medium-sized plastic debris is often difficult to identify using conventional methods due to variations in color, shape, and reflectance. This study proposes an image-processing-based approach that combines thresholding and contour detection techniques to improve the accuracy of detecting plastic objects on floor surfaces. The initial stage involves converting the image into a color space that is more stable under varying illumination, such as HSV or grayscale, to reduce the influence of lighting intensity. Subsequently, adaptive thresholding is applied to separate plastic objects from the background by using dynamic threshold values tailored to the image’s conditions. The segmentation results are refined through morphological operations such as opening and closing, enabling the removal of small noise and enhancing the clarity of object boundaries. The core stage of the system employs contour detection to extract object shapes and areas, allowing the identification of plastic waste based on size, perimeter, and specific geometric characteristics. Experiments were conducted under different lighting conditions and various floor types, and the results demonstrate that the proposed approach successfully detects plastic debris with satisfactory accuracy and relatively fast processing time. Therefore, this method is suitable for implementation in robotic cleaning systems, indoor cleanliness monitoring devices, and other computer vision applications requiring real-time and efficient object detection.

Fortuna Furniture still manages its inventory manually, which causes many problems, including delayed reports, inaccurate information, and the potential for lost records. These issues affect the quality of decision-making and operational efficiency. This service aims to build a web-based inventory information system that improves speed, accuracy, and integration in inventory management. The system development process follows the Waterfall model SDLC approach, with requirements analysis, design, implementation, and testing supported by interviews, observation, and documentation. The results of the activity show that the developed system can reduce input errors, speed up the process of recording incoming and outgoing goods, and enable real-time stock monitoring. Additionally, the report generation process becomes more efficient and easier for management to access. Overall, the use of this information system significantly improved the efficiency of Fortuna Furniture's inventory management and demonstrated the importance of digitalization in helping businesses run more smoothly.

This study aims to analyze and compare rice inventory valuation using the FIFO, FEFO, and Average methods in determining the cost of goods sold (COGS) at UD. Rahayu Indah. This study uses a quantitative descriptive approach with a perpetual inventory recording system. Data were collected through observation, interviews, and documentation from January to December 2024. The results show that each method produces different COGS values: the FIFO method produces the lowest COGS, followed by FEFO, while the Average method produces the highest COGS. This difference is influenced by cost allocation based on the order of goods in and out and price fluctuations during the production period. These findings indicate that the FIFO method is the most effective method to be applied at UD. Rahayu Indah because it reflects the logical physical flow of goods, supports cost efficiency, and increases the company's gross profit. In addition, this method is also in line with the company's operational characteristics, which have stable purchasing patterns and are in accordance with the principles of PSAK No. 14 on inventory. The results of this study are expected to assist UD. Rahayu Indah's management in determining an inventory valuation strategy that is efficient, accurate, and supports business sustainability.

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the economy of Ketapang Regency but still face challenges in financial recording and management. Many MSME actors have not yet utilized digital technology optimally, leading to manual bookkeeping processes that are prone to errors. This study aims to develop a web-based financial bookkeeping application using the User-Centered Design (UCD) approach, focusing on user needs. The UCD method was applied through four stages: understanding the context of use, specifying user requirements, designing solutions, and evaluating the results. The developed application includes key features such as product management, supplier management, sales recording, receipt printing, and financial reporting. Based on usability testing involving 25 respondents, the application achieved an average satisfaction level of over 85% across aspects of learnability, efficiency, memorability, error handling, and satisfaction. The findings indicate that the application effectively supports MSME actors in recording financial transactions more efficiently, accurately, and reliably. Future improvements may include the integration of digital payment systems, enhanced data security, and interactive graphical financial analysis features.

The manual submission of employee complaints often leads to slow handling, disorganized documentation, and limited transparency regarding complaint progress. These issues hinder internal communication and reduce the effectiveness of administrative processes. This study aims to design and implement a Web-Based Employee Complaint Submission System using PHP and the Bootstrap framework to improve efficiency and accuracy in managing complaints. The system supports three main categories of complaints: payroll, occupational safety and health, and work facilities. It also enables employees to track complaint status through request, approved, and rejected indicators. Administrators can manage user accounts and generate official follow-up letters. Implementation results show that the system improves data recording, enhances documentation order, and increases transparency in complaint handling. Overall, the system facilitates more structured, efficient, and traceable communication between employees and management, supporting better corporate governance.