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Enforcement of discipline among the State Civil Apparatus (ASN) is an important component in maintaining professionalism and efficiency of public services. This study aims to analyze the effectiveness of disciplinary punishment enforcement in improving ASN discipline at the Batam Municipal and Special Port Authority (KSOP) Office. The background of this research includes various challenges in enforcing ASN discipline, such as long and bureaucratic procedures, low awareness of discipline, and political intervention. The research method used is normative juridical using secondary data through library research, and also an empirical juridical approach with primary data through field research. Primary data collection was carried out through in-depth interviews, observations, and document analysis. The research respondents consisted of Batam KSOP employees, related officials, and other parties related to discipline enforcement in the environment. The results of the study show that the effectiveness of disciplinary enforcement in KSOP Batam is still not optimal. Convoluted enforcement procedures, lack of employee understanding of the importance of discipline, and political intervention were the main obstacles found. In addition, limited human resources and facilities also hinder the effective discipline enforcement process. This study also found that efforts to simplify procedures, increase socialization and education, and strengthen transparent supervision can increase the effectiveness of disciplinary punishment enforcement. Suggestions include the need for bureaucratic reform to simplify discipline enforcement procedures, the implementation of training and education programs on an ongoing basis, and the establishment of an independent internal oversight unit. Additionally, it is important for governments to ensure that discipline law enforcement is free from political interference and supported by adequate resources. With these steps, it is hoped that the discipline of ASN at KSOP Batam can be improved, which will ultimately contribute to improving the quality of public services and the reputation of government agencies.

The Sea and Coast Guard Base (PLP) plays a vital role in maintaining maritime security and safety in Indonesia, especially in strategic waters such as the Riau Islands. However, the implementation of the PLP's authority in carrying out its duties at the Tanjung Uban Class II PLP Base has not run optimally. This study aims to analyze the authority of the PLP from a juridical and sociological perspective, as well as identify the obstacles faced and provide recommendations to overcome them. The research methods used are normative juridical and empirical sociology. The normative juridical method is used to analyze various laws and regulations that are the legal basis for the authority of the PLP, such as Law Number 17 of 2008 concerning Shipping, Regulation of the Minister of Transportation of the Republic of Indonesia Number PM 119 of 2021 concerning the Organization and Work Procedures of Marine and Coast Guard Bases, Decree of the Director General of Hubla Number 13/VIII/DV-05 of 2005 concerning the Working Area of Marine and Coast Guard Bases and the Decree of the Director General of Sea Transportation Number KP.867/DJPL/2020 concerning the Patrol of the Marine and Coast Guard Unit of the Directorate General of Sea Transportation. Empirical sociological methods are used to collect data through interviews and direct observations in the field to understand the implementation of PLP authority and the obstacles faced. The results of the study show that limited human resources and equipment, lack of coordination between agencies, inadequate infrastructure, and complex bureaucracy are the main obstacles in the implementation of PLP authority in the Tanjung Uban Class II PLP Base. In addition, the low legal awareness among the maritime community is also a significant challenge. Based on these findings, this study provides several suggestions, including increasing recruitment and training of personnel, procurement and maintenance of patrol boats and supporting equipment, the formation of an inter-agency coordination team, the construction of adequate port facilities, and socialization and education to increase public legal awareness. This research is expected to contribute to strengthening policies and strategies for the implementation of PLP authority, so as to be able to increase effectiveness and efficiency in maintaining maritime security and safety in Indonesian waters.

Modern agriculture has experienced a significant transformation with the introduction of mechanization technology, one of which is the use of combine harvesters. This machine has a crucial role in increasing the efficiency and productivity of crop harvests, especially in the cultivation of cereal crops such as rice, wheat and corn. This research aims to determine the effect of using a combine harvester on lowland rice productivity. This research was carried out from September to October 2023 in Tanjung Alai Village. The data analysis used in this research is linear regression analysis to analyze the effect of yield loss due to the use of a Combine Harvester (CH) on productivity. The research results showed that the use of a Combine Harvester in Tanjung Alai Village, Mukomuko Regency was able to increase rice productivity by 487.56 kg/ha (11.21%) compared to harvesting without using a Combine Harvester. The T Test results show a significant value of 0.000, meaning that the significant value ˂ ɑ 0.05 indicates that the yield loss variable when harvesting using a Combine Harvester has a real or significant effect on rice productivity. Based on the regression equation formed, every 1% reduction in yield loss when harvesting using a Combine Harvester will increase rice productivity by 79,221 kg

Urbanization has significantly impacted air quality in cities, with vehicular emissions being a major contributor to pollution. This study explores the potential benefits of electrifying urban transportation, specifically through the adoption of electric vehicles (EVs). The findings indicate that EVs substantially reduce key pollutants such as CO₂, NOx, and PM₂.₅, improving urban air quality and mitigating climate change. The analysis shows that EV adoption can lead to a 50% reduction in CO₂ emissions in high EV adoption scenarios (70% EVs). Additionally, EVs are more energy-efficient than conventional vehicles, consuming significantly less energy per kilometer. This transition not only reduces dependence on fossil fuels but also supports sustainable urban development. Furthermore, the study highlights the public health benefits of electrification, with reduced levels of harmful pollutants leading to lower incidences of respiratory and cardiovascular diseases. Public health surveys reveal strong support for EV adoption, with respondents believing it would significantly improve air quality and health outcomes. In conclusion, the electrification of urban transportation presents a multifaceted approach to environmental sustainability, energy efficiency, and public health improvement.

Combinatorial optimization is a fundamental area in operations research and computer science, focusing on identifying optimal solutions from a finite set of possibilities. This study explores the integration of branch and bound methods with heuristic algorithms to address optimization problems in graph theory and discrete mathematics. Python was employed for algorithm implementation due to its flexibility and comprehensive computational libraries, enabling efficient data analysis and visualization. Several benchmark problems were examined, including the Traveling Salesman Problem (TSP), Minimum Spanning Tree (MST), and Graph Coloring. Simulations were conducted using datasets of varying sizes (small, medium, and large) to evaluate performance across different scales. The results demonstrate that the hybrid approach achieves a balance between solution quality and computational efficiency, outperforming brute-force methods in terms of speed while maintaining near-optimal accuracy. Tabulated results and graphical comparisons highlight the reduction in computation time and improved scalability of the proposed method. The findings suggest that combining systematic search strategies with heuristics offers a practical and effective framework for solving complex combinatorial optimization problems. Recommendations for future research include testing scalability with larger datasets, incorporating advanced metaheuristics, and applying the approach to real-world domains such as logistics and network design.

In the digital era, the advancement of information technology is crucial for enhancing operational efficiency in retail businesses. This study aims to design and develop a sales and inventory information system with a shelf mapping feature for Toserba Decky, which faces challenges in managing stock and manual transactions. The methodology employed is the Waterfall approach, encompassing requirements analysis, design, implementation, and system testing. Data was collected through direct observation, literature review, and analysis of the store's shelf layout. The findings indicate that the developed system can improve data accuracy, reduce recording errors, and expedite product searching. The implications of this research suggest that an effective information system in managing transactions and inventory can enhance operational efficiency and customer satisfaction. This study recommends regular system updates and technical support to ensure optimal system performance and security.    

This review aims to investigate the role of forecast dispersion and accuracy in explaining cross-sectional return anomalies in financial markets. By synthesizing recent theoretical and empirical research, the study examines how differences in information precision among investors lead to heterogeneous beliefs, which in turn affect asset prices and returns. The methodology involves a comprehensive literature review to identify key findings and theoretical frameworks that link forecast dispersion to market dynamics. Results indicate that higher forecast dispersion, associated with greater uncertainty and risk, correlates with higher expected returns as compensation. Conversely, accurate forecasts enhance market efficiency by reducing information asymmetry, thereby mitigating anomalies. The study also highlights theoretical models that explain anomalies like returns to skewness and disagreement through the lens of forecast dispersion. Empirical evidence supports these models, demonstrating the significant impact of forecast dynamics on asset pricing anomalies. The review concludes by emphasizing the need for further research to refine models capturing forecast dynamics and exploring the behavioral biases influencing forecast accuracy and dispersion. Understanding these factors is crucial for improving investment strategies, market efficiency, and risk management practices.

This research explores the relationship between public information precision, borrower risk-taking behavior, and financial reporting regulations. It examines how varying levels of accounting disclosures influence creditor-borrower dynamics in financial markets. Enhanced precision in public information, such as accounting earnings, promotes market efficiency by reducing information asymmetry and improving creditors' ability to accurately assess borrower creditworthiness. While higher precision generally mitigates borrower risk-shifting tendencies, regulatory context and economic conditions modulate these effects. This literature review systematically identifies and analyzes peer-reviewed articles on forecast dispersion, accuracy, and their implications for cross-sectional return anomalies in financial markets. The findings reveal that higher forecast dispersion is linked to greater uncertainty and perceived risk, leading to higher expected returns, while accurate forecasts reduce information asymmetry and improve market efficiency. Differences in forecast precision significantly contribute to market anomalies. In conclusion, forecast dispersion and accuracy are critical in explaining cross-sectional return anomalies. Future research should refine models, explore behavioral biases, and evaluate technological advancements, emphasizing balanced financial reporting regulations to harness transparency benefits while mitigating potential costs during economic expansions.

Optimizing Windows-based operating systems for databases in Cloud and Edge Computing environments is very important to increase data management efficiency and performance. In this study, we discuss ways to optimize Windows in both environments. In the Cloud environment, the main focus is on data management using services such as Google Drive, while in the Edge environment, optimization is carried out using Windows IoT Core and Windows IoT Enterprise. Of these two, we optimize Windows IoT Enterprise more because it is more directed towards Edge computing. Our research results show that by implementing the right optimization and efficient performance results, database performance can be significantly improved, which provides great benefits for individual users and society

The Online Regional Investment Information System (SI INVEST OKE) is an innovation in licensing services in Demak Regency that aims to accelerate and simplify the licensing application process. This system replaces the previous offline application, SIMPPT, and provides technology-based services that can be accessed from anywhere. This study uses a descriptive analytical method with a qualitative approach to evaluate the implementation of SI INVEST OKE using Leavitt's Model (1965), which examines the relationship between four main components: tasks, human resources, technology, and organizational structure. Data were collected through in-depth interviews with DINPMPTSP employees and service users, direct observation at the DINPMPTSP office, and analysis of related documents. The findings show that the implementation of SI INVEST OKE has succeeded in reducing service time, increasing public satisfaction, and providing efficiency in licensing management. However, challenges such as limited technological infrastructure in remote areas and human resource skills are still obstacles that need to be overcome. The main recommendations from this study include increasing human resource capacity, expanding technological infrastructure, and developing more supportive regulations.

This research explores the use of iterative methods in conjunction with the Finite Difference Method (FDM) for solving partial differential equations (PDE). The central challenge addressed is the computational inefficiency and slow convergence that often arise when utilizing traditional numerical methods, particularly in large-scale systems. The study aims to develop a more efficient iterative approach to solve PDEs by minimizing computational time while ensuring the stability of the obtained solutions. The primary methods proposed include iterative solvers such as Gauss-Seidel and Successive Over-Relaxation (SOR), which are applied to numerical solutions derived from FDM. The research demonstrates that iterative methods, especially SOR, achieve faster convergence with fewer iterations compared to conventional methods like the Finite Element Method (FEM), which tends to be slower and more resource-intensive for large-scale problems. The study highlights the advantages of iterative solvers in efficiently handling large, sparse linear systems and reducing computational costs. In addition, it shows that these methods are capable of providing stable solutions, thereby maintaining accuracy with significantly lower computational effort. The results suggest that iterative methods, when applied in combination with FDM, offer a practical and scalable solution for solving complex PDEs. These methods are especially beneficial in engineering and theoretical physics applications where large-scale simulations are prevalent. The study concludes with recommendations for future research, which should focus on further optimizing solver parameters, exploring hybrid approaches, and extending the methods to more complex PDEs with non-linearities or irregular geometries. By doing so, these techniques could contribute to even more efficient and practical solutions for real-world applications.

Urban drainage systems face mounting pressure due to the combined impacts of rapid urbanization and climate change. The expansion of impervious surfaces and altered precipitation patterns contribute to increased stormwater runoff, exacerbating flood risks and water quality issues in cities. Traditional drainage systems, focused primarily on controlling water volume, are insufficient to address the growing complexity of urban drainage challenges. This study proposes Sustainable Urban Drainage Systems (SUDS) that integrate flood management, water quality improvement, and climate resilience. By incorporating nature-based solutions such as permeable pavements, green roofs, and rain gardens, these systems aim to reduce runoff, enhance groundwater recharge, and mitigate the negative effects of urbanization. Through a Multi-Criteria Decision Making (MCDM) framework, this research evaluates various drainage solutions based on technical, socio-economic, and environmental criteria. The findings indicate that SUDS outperforms traditional systems in flood mitigation, water quality control, and climate resilience, highlighting their importance in adapting to changing climatic conditions. This paper emphasizes the need for sustainable drainage solutions to ensure long-term urban resilience and improve the overall quality of urban environments.

This research aims to develop a web-based Mosque Management Information System (SIMM) to manage the administrative and operational activities of mosques. The method used in this research is the Systems Development Life Cycle (SDLC) Waterfall model. The SDLC phases include Project Planning Phase, Analysis Phase, Design Phase, Implementation Phase, and Support Phase. This research was conducted at Al Hikmah Mosque, located in Grand Samara Residence, Dusun Kopo, Klari Village, Karawang District. Data and information were collected through surveys and interviews with mosque administrators. The results show that the developed web-based SIMM can improve efficiency in data management, enhance coordination among stakeholders, and increase transparency in financial management. The system was well received by mosque administrators and is expected to improve the overall quality of mosque management. Additionally, this SIMM is expected to provide better services to the congregation and increase the accountability of mosque administrators.

This community service project aimed to support the development of the "Kerupuk Santoso" MSME in Karangkembang Village, Lamongan Regency, East Java, through training in business management and digital marketing. While this MSME has significant growth potential, it faces various challenges, including limitations in marketing and management. Through a series of training sessions and mentoring, the MSME operators successfully improved their skills in management and digital technology utilization to expand their market reach. The results of this project show a significant increase in operational efficiency and product competitiveness in a broader market. The support from the local community and the active involvement of KKN students played a crucial role in the success of this program. This initiative is expected to have a long-term positive impact on the local economy and the well-being of the community.

The adoption of Robotic Process Automation (RPA) has emerged as a crucial strategy for medium-sized enterprises (SMEs) to streamline back-office operations, enhance productivity, and reduce operational costs. RPA involves the use of software robots to automate repetitive, rule-based administrative tasks, allowing employees to focus on more complex, value-added activities. This study explores the implementation of RPA in medium enterprises, focusing on its impact on cost efficiency, administrative workload reduction, and operational performance. The research uses a case study approach, analyzing medium enterprises that have adopted RPA to assess the effectiveness of automation in improving business processes. Data collection methods include interviews, surveys, and company reports to evaluate how RPA affects workload, accuracy, and cost savings. The findings indicate that RPA significantly reduces manual administrative tasks, leading to faster processing times, lower error rates, and substantial cost savings. Employees in enterprises that adopted RPA reported increased job satisfaction due to the reduction of monotonous tasks and the opportunity to engage in more strategic work. However, challenges such as employee resistance, data security concerns, and system integration complexities were also identified. The study compares RPA’s impact with traditional manual processes, highlighting improvements in speed, accuracy, and overall cost efficiency. Additionally, the study compares RPA adoption across industries such as manufacturing, retail, and service, revealing sector-specific challenges and successes. The paper concludes by emphasizing the practical implications for SMEs, suggesting that RPA can optimize business operations and urging further research on its long-term effects on employee roles and organizational culture.

This study evaluates the policy implementation of the face recognition system at Surabaya Gubeng Station as a digital innovation in public service by PT Kereta Api Indonesia (Persero). Using a qualitative approach and the policy evaluation model by William N. Dunn, the study assesses six key indicators: effectiveness, efficiency, adequacy, responsiveness, accuracy, and equity. The findings indicate that the system is effective in accelerating the boarding process, reducing queues, and improving passenger convenience. Efficiency is achieved through reduced staff workload and automated identity verification. However, several challenges remain, including technical disruptions, data input errors, and low digital literacy among users. Personal data protection is also a concern as most users are not fully aware of how their biometric data is managed. Therefore an adaptive governance strategy is needed, involving infrastructure improvement, staff training, public education, and greater transparency in data policy. With these measures, the face recognition system can serve not only as a tool for technical efficiency but also as a form of inclusive and sustainable public service transformation.

This research aims to analyze the role of digital communication in improving business efficiency by focusing on the use of digital communication tools such as email, chat, and collaboration platforms. The research object consisted of 10 STIE Ganesha students of the employee class who were selected as respondents to provide insight into their experience in using digital communication tools in the context of their work. This research was carried out in May 2024 using a qualitative approach, where data was collected through in-depth interviews and thematic analysis to identify key patterns and themes related to the effectiveness of digital communication compared to traditional communication methods. The results showed that digital communication tools significantly improved operational efficiency for working students, allowing them to complete tasks more quickly and organized. However, the findings also reveal significant challenges, such as information overload and notification distractions, which can reduce productivity and focus. Therefore, while digital communication offers many advantages, it is important for individuals to develop effective management strategies to address these negative potentials, such as notification management and wise time allocation. The implications of this study underscore the importance of a deep understanding of digital communication tools and their effective application to maximize productivity in the modern business environment.

The aim of this research is to analyze the efficiency of raw material inventory control and the application of the Material Requirement Planning method to control soybean raw material inventory at Mr Heri's Tofu Factory. The type of data used is qualitative data and quantitative data. Data sources in research use secondary data and primary data. Data collection methods used were interviews, observation and documentation. The data analysis technique used is to streamline raw material costs using the Material Requirement Planning (MRP) technique. The research results show that the raw material inventory costs according to company policy of IDR 1,553,712 are not efficient, because the total raw material inventory costs are greater than the LFL method of IDR 240,000, EOQ of IDR 297,914 and POQ of IDR 240,000. Based on this, hypothesis 1 which states that "It is suspected that the raw material control system for Mr Heri's Tofu Factory is not efficient", has been proven to be true. Hypothesis 2 which states that "It is suspected that the application of the Material Requirement Planning method can streamline the costs of controlling raw material inventory at Mr Heri's Tofu Factory", has been proven to be true.

This research aims to analyze the opportunities and challenges of implementing financial technology (Fintech) in Micro, Small, and Medium Enterprises (MSMEs) in Banyumas Regency. Banyumas was chosen as the research location because it has good potential for the development of MSMEs. This study uses a qualitative descriptive approach, analyzing data obtained from information and interviews with MSME actors. Based on the research results, it is concluded that MSME actors have a good understanding of fintech as a financial technology innovation that can help operational efficiency for MSMEs. MSME actors recognize the importance of using fintech today; they experience ease and efficiency in payment transactions, potential for sustainable growth, increased competitiveness in the digital economy era, and the potential to boost sales. However, in its implementation, MSMEs face several obstacles and challenges in using fintech, including security and privacy factors, the lack of interest and understanding of fintech usage by consumers, the risk of cybercrime, and limited internet access. Therefore, support from various parties such as the government, industry, and the wider community is needed to optimize the benefits of fintech.

Advances in information technology have become a major influence on society in meeting needs, quality and convenience. One example of technological progress is online sales. E-commerce or online shops can make it easier for people to shop with time efficiency, accuracy and quality and can make it easier for the shop to sell because it can promote the products it sells more widely and get maximum profits. This research focuses on designing the UI/UX for cosmetic sales at beauty cosmetic stores. Researchers found problems in beauty cosmetic stores in that store management was still manual, only using social media as promotion without an online sales platform so that the income obtained from sales was not optimal. The method used in designing the UI/UX for selling cosmetics at this beauty cosmetic shop is using the prototype method. The results of this research are the UI/UX design for selling cosmetics at beauty cosmetic shops which can make it easier for beauty cosmetic shops to market their products. It is hoped that this learning media can increase people's interest in shopping at beauty cosmetic stores.