Publication Search

This investigation examines the implementation of linguistic politeness in English as Foreign Language (EFL) instruction in Karawang, with particular emphasis on faculty-student interactions. Utilizing an ethnographic qualitative methodology, the research encompasses one faculty member and thirty-five, first-semester students. Data acquisition was conducted through non-participant classroom observations and semi-structured in-depth interviews. The findings demonstrate that the faculty member systematically implemented politeness strategies through indirect communication and face-threatening acts management. The incorporation of Sundanese cultural values in instruction was manifested in the utilization of address systems and modifications in communication approaches. The implementation of politeness significantly contributed to the enhancement of students' communicative competence and the establishment of a conducive learning environment. This research underscores the significance of integrating linguistic politeness and indigenous cultural values in EFL instruction to facilitate pedagogical effectiveness.  

The increasing frequency and severity of tsunamis in coastal areas underscore the urgent need for efficient Tsunami Early Warning Systems (TEWS). This research aims to optimize TEWS by integrating fast computational tsunami wave modeling to enhance prediction speed and accuracy. The study utilizes numerical simulations employing finite volume methods, along with GPU acceleration, to model tsunami wave propagation and its impact on coastal areas. Machine learning techniques, such as regression trees, are incorporated to analyze large datasets of pre-computed tsunami simulations for accurate forecasting. The results reveal that by applying rapid computational methods, detection time can be reduced by up to 7 minutes, particularly for near-field tsunamis. This significant time-saving enables more effective evacuation procedures and better disaster mitigation efforts. In comparison to conventional systems, the fast computation model also provides more accurate predictions, including tsunami heights and arrival times. The implications of these findings suggest that fast computational methods can substantially improve the current TEWS, allowing for quicker and more reliable tsunami warnings. Moreover, the integration of advanced machine learning techniques ensures the system's adaptability and robustness in predicting tsunami behaviors based on varying data inputs. The potential for implementing this model in tsunami-prone regions worldwide is considerable, offering an improved approach to tsunami disaster preparedness and response. By reducing detection time and enhancing prediction accuracy, the optimized TEWS can significantly minimize loss of life and infrastructure damage, making it a valuable tool for global disaster management strategies.  

The purpose of integrating artificial intelligence (AI) technology into campus smart parking management systems is to improve user comfort, safety, and efficiency. To control car traffic in real-time, the system combines technologies including computer vision, machine learning, and the Internet of Things (IoT). Automatic vehicle detection, license plate recognition, parking lot availability prediction, and ideal vehicle flow regulation are some of the key characteristics. The system can effectively recommend parking to users through a mobile app by using pattern analysis and historical data. The implementation results showed a 25% reduction in traffic in the university's parking area and a 30% increase in parking time efficiency. According to the findings of the study, applying AI technology in parking management can be a creative way to overcome the difficulties associated with facility management in higher education environments.

The increasingly dynamic global financial landscape demands effective risk management strategies to ensure financial stability and institutional sustainability. Two critical approaches, risk financing transfers and risk retention, offer complementary solutions. Risk financing transfers allow institutions to redistribute financial risks to third parties through mechanisms such as securitization and Credit Risk Transfers (CRTs), improving market efficiency. In contrast, risk retention emphasizes accountability by require institutions to retain a portion of the risks, fostering market discipline and investor confidence.This study employs a Semantic Literature Review (SLR) to analyze the interaction between these approaches, focusing on mechanisms like securitization, contract design, and macroprudential policies. By reviewing ten peer reviewed articles published between 2015 and 2024, key themes and challenges related to systemic risks, moral hazards, and regulatory gaps are identified. Thematic analysis, supported by tools like NVivo, reveals the potential of these mechanisms to enhance financial stability when implemented within a robust regulatory framework.The results highlights that while risk financing transfers increase flexibility and market efficiency, they May exacerbate moral hazards without sufficient risk retention. Macroprudential policies and accurate risk pricing is crucial in addressing systemic risks, particularly in sectors like shadow banking and climate vulnerable regions. The study also underscore the importance of transparent contract design and the integration of innovative tools, such as geospatial data and machine learning, to support fair and efficient risk distribution.In conclusion, balancing market efficiency and systemic risk mitigation is imperative.While​ risk retention strengths accountability and oversight, effective integration with risk financing transfers is necessary to create a sustainable and resilient financial system.This​ review provides valuable insights for policy makers and practitioners in addressing emerging financial challenges.

In the era of globalisation and rapid technological development, developing the competencies of teachers and education staff is key to improving the quality of education. This article discusses various strategies for competency development in education human resource management (HRM), with a focus on teachers and education staff. Adopting an evidence-based approach identifies effective methods for training and professional development, including the utilisation of technology, online courses, and experiential learning. In addition, it explores the critical role of constructive feedback and continuous evaluation in the competency development process. The research underscores the importance of integration between HRM theory and daily educational practice to achieve optimal results. The results of this article are expected to provide practical guidance for educational institutions in designing effective development programmes to improve teacher and staff performance and advance the education system as a whole.

This article examines the importance of building a good organizational culture within school internal administration framework. It aims to investigate efficient methods for building and maintaining an organizational culture that supports student and educator growth. Through an in-depth literature review, several key elements are identified, including visionary leadership, shared vision-mission formulation, and staff empowerment. The article emphasizes the importance of creating a cooperative work environment to foster innovation and creativity. Key aspects examined include learning-supportive physical space design, positive psychological atmosphere creation, reward systems, and conflict management strategies. The research also discusses main obstacles such as resistance to change and generational differences, while presenting practical solutions to address them. In conclusion, building a good organizational culture is an ongoing effort requiring dedication from all parties involved. This research provides important perspectives for education practitioners and policymakers in improving overall educational standards.

Educational management plays a strategic role in determining the success of learning processes in various educational institutions. Evaluation and accountability are two interrelated key elements in shaping an effective, transparent, and sustainable education system. This study aims to develop an adaptive and responsive educational management concept to meet contemporary demands and provide strategic recommendations for educational institutions in improving learning quality. Using a qualitative approach with a descriptive-analytical design, this research finds that the integration of systematic evaluation and strong accountability is a fundamental aspect of educational management. Evaluation provides in-depth data on learning effectiveness, while accountability ensures that every component of the educational system takes responsibility for the outcomes achieved. Together, they significantly contribute to creating an educational management mechanism oriented toward continuous quality improvement. 

This study presents the development and evaluation of an automatic passenger counting system for public buses using the YOLOv8 algorithm based on Convolutional Neural Networks (CNN). Accurate passenger counting plays a crucial role in optimizing public transportation operations, as it enables effective capacity management, reduces operational costs, and improves overall passenger comfort. Conventional manual counting methods are often inefficient, time-consuming, and prone to human error, particularly in high-density urban transportation environments. Therefore, an automated and intelligent solution is required to support real-time monitoring and operational decision-making. The proposed system employs deep learning-based object detection to identify and count passengers from video streams captured by cameras installed inside buses. Two camera positions, namely front and rear views, were evaluated to assess system performance under different visual conditions. The experimental results show that the system achieves high detection accuracy in the front camera view, with a confidence score of 0.82, indicating reliable performance in scenarios with minimal object occlusion. In contrast, the rear camera view demonstrates slightly lower accuracy, with a confidence score of 0.76, mainly due to increased object overlap and variations in lighting conditions. These findings emphasize the importance of appropriate camera placement and environmental consideration in improving detection reliability. In addition, the implementation of the proposed system enables real-time monitoring of passenger flow, which supports dynamic scheduling, demand-based route planning, and efficient fleet management. Accurate passenger data allows transportation operators to optimize service allocation, reduce congestion, and enhance overall service quality. Overall, this study contributes to the development of intelligent transportation systems by demonstrating the practical applicability of deep learning-based passenger counting solutions. The proposed approach offers strong potential for real-world deployment in smart city environments, supporting the creation of more sustainable, efficient, and passenger-oriented public transportation services.

The purpose of this study is to conduct a literature review of previous research on Information Technology and Higher Education Performance from 2020 - 2024. Information Technology Systems as a tool to help the performance of higher education, which is widely used in universities to improve their organization. this study uses SLR which presents quantitative data on Information Technology and Higher Education Performance there are measurements used, namely journals, variables, and theories as well as the field of science reaserch approach. The study results showed 30 articles from accredited national journals and national journals. The topic of higher education performance is influenced by information technology variables, quality assurance, learning perspectives, growth, internal perspectives. The theory used is the information technology system in higher education performance. State universities and private universities are researching a lot about Information Technology. But only a few universities use widely used Information Technology Systems such as Academic Management Information Systems, Sevima Platform, and E-Learning. Although universities have successfully implemented information technology systems, the main challenges faced are the digital divide, access to technology, and security. This research provides insights, benefits, and constraints in implementing and recommending Information Technology Systems and College Performance.  

The integration of IT Governance and expert system design offers transformative benefits for enhancing library user services. This research employs the COBIT 5.0 framework to align IT strategies with library objectives while developing an expert system tailored for personalized recommendations. The findings indicate that the expert system significantly improves operational efficiency, service accuracy, and user satisfaction by using user profiles to recommend relevant materials and streamline the borrowing process. Testing revealed high user satisfaction levels, with 96.6% finding the system effective and 100% confirming its efficiency. Additionally, IT Governance ensures strategic integration between technological infrastructure and service quality objectives, enabling data-driven decision-making. The study also highlights challenges, such as the need for robust data management and user training, suggesting areas for future improvement. Recommendations include incorporating machine learning to enhance system intelligence, conducting regular evaluations to maintain system relevance, and testing the scalability of this approach across various types of libraries. By integrating IT Governance with an expert system, this research sets a strong foundation for modernizing library services to better meet user expectations in the digital era.

In the midst of the climate crisis and environmental damage that is increasingly real, the role of schools as educational centers is increasingly crucial. Not only producing a smart generation, schools have a great responsibility to become a motor of change towards a sustainable future. Green School Bali is an example of the application of the concept of green school that integrates the principle of sustainability in the design of buildings and the education system. By using natural materials such as bamboo that are environmentally friendly and sustainable, this school prioritizes energy conservation, natural lighting, natural ventilation, and efficient management of resources. This study aims to analyze the application of sustainable architecture principles in Green School Bali, using qualitative methods through secondary data analysis from documentation, reports, and related literature. The results show that building design not only minimizes negative impacts on the environment, but also supports the goals of continuing education. Green School Bali is an innovative model to create a learning environment that is in harmony with nature.

In the digital era, the utilization of information technology has become a primary need to support various aspects of education. One of the innovations implemented in educational institutions is the use of e-learning platforms, which allow learners to study flexibly without being hindered by distance and time. Universitas Amikom Purwokerto has developed the E-Learning Support System (ELLS) website as an online learning tool accessible by students and lecturers. This study aims to analyze the service management of ELLS using the ITIL V3 framework, which provides a structured guide in managing and optimizing services to better meet user needs in a sustainable manner. The methodology used includes observation, interviews, and surveys distributed to service users. The results show that the implementation of ITIL V3 can improve service effectiveness, reduce the risk of disruptions, and provide a positive experience for users. This research is expected to provide recommendations for improving e-learning service management at Universitas Amikom Purwokerto and serve as a reference for other educational institutions looking to enhance the quality of their services.

Classroom management is a conscious effort to organize learning process activities systematically, including the preparation of teaching materials, provision of facilities and infrastructure, organizing learning spaces and creating a conducive learning atmosphere so that learning objectives can be achieved. Classroom management efforts lead to the preparation of learning materials, learning facilities and infrastructure, learning space arrangements, controlling student behavior, and improving student achievement and grades. The implementation of classroom management will create an effective, varied, and fun learning atmosphere. The purpose of the research conducted intends to find out (1) To what extent is the implementation of classroom management. (2) Whether the learning process is effective. (3) What are the inhibiting and supporting factors in implementing classroom management. (4) And what efforts are made by teachers and schools in improving the effectiveness of classroom management. The results showed that classroom management has not been carried out optimally, the teacher's teaching method is still monotonous so that it makes students less interested in listening to the material. Then there is still a lack of student discipline. Although the implementation of classroom management is still not optimal, teachers remain enthusiastic and continue to strive to do and implement classroom management optimally, so that what is the goal of the school will be achieved properly. The efforts that teachers will make in implementing classroom management in order to increase the effectiveness of learning are by preparing administrative tasks properly, using varied learning methods and media. And teachers apply student discipline.    

Classroom management is a conscious effort to organize learning process activities systematically, including the preparation of teaching materials, provision of facilities and infrastructure, organizing learning spaces and creating a conducive learning atmosphere so that learning objectives can be achieved. Classroom management efforts lead to the preparation of learning materials, learning facilities and infrastructure, learning space arrangements, controlling student behavior, and improving student achievement and grades. The implementation of classroom management will create an effective, varied, and fun learning atmosphere. The purpose of the research conducted intends to find out (1) To what extent is the implementation of classroom management. (2) Whether the learning process is effective. (3) What are the inhibiting and supporting factors in implementing classroom management. (4) And what efforts are made by teachers and schools in improving the effectiveness of classroom management. The results showed that classroom management has not been carried out optimally, the teacher's teaching method is still monotonous so that it makes students less interested in listening to the material. Then there is still a lack of student discipline. Although the implementation of classroom management is still not optimal, teachers remain enthusiastic and continue to strive to do and implement classroom management optimally, so that what is the goal of the school will be achieved properly. The efforts that teachers will make in implementing classroom management in order to increase the effectiveness of learning are by preparing administrative tasks properly, using varied learning methods and media. And teachers apply student discipline.    

The policy for Independent Learning Independent Learning Campus (MBKM) internship activities is an example of a new idea in higher education that provides flexibility to students. In accordance with the mandate of Permendikbud Number 03 of 2020 concerning National Higher Education Standards, the Independent Learning Independent Campus (MBKM) was formed. Students of the IAIN Palangka Raya Islamic Education Management Study Program complete an internship assignment for one semester. The purpose of this program is to provide opportunities for students to apply the theories and knowledge that have been learned in lectures to the workplace situation. The method used is mentoring conducted by one Internship Assistance Lecturer to 4 participants for one semester. This internship activity is located at the Regional Staffing Agency of Central Kalimantan Province. The results of the office internship activities that have been carried out, student interns can do work practices and learn firsthand how the office administration system and staffing services at the BKD of Central Kalimantan province.

And its education management has a backbone.play a role in any school's performance and reputation. Schools use a variety of Strategies for maintaining higher educational quality than their competitors. In a similar myriad, The current study evaluated the success factors and variables that followed. STAISA for the effective application and practise of education management. system. The study had investigated Various aspects, including the curriculum, learning facility, and financing School infrastructure, connection, or communication from society, Education management instructors' quality, experience, training, and course offerings and qualification, among others. The study examined STAISA education management. The system employs a qualitative research approach and an interview tool for Data gathered from the administration authorities, including the principal. Vice-principal and other school decision-makers. Data Analysis The technique used was thematic analysis and thought mapping. The findings imply that.The school has been successful at Implemented a rigorous academic curriculum and connected departments. Putting emphasis on cooperation and communication among all stakeholders.

The Indonesian Islamic educational system is critical to shaping students' moral and intellectual development. Efficient administration is essential for improving educational outcomes, fostering a pleasant learning environment, and sustaining Islamic principles. As a result, the primary goal of this study is to assess the efficiency of the Islamic management system in Islamic schools by gathering information from the management teams of the selected schools. The study used a qualitative research design to collect important information from the target audience. The study's findings show the need of excellent administration in improving Islamic curricula in Indonesian educational institutions. A complete plan that blends creative teaching methods with efficient administration is required to foster a strong and vibrant learning environment. However, the results have limited generalisability to other ethnic or educational backgrounds because they are unique to Indonesia's Islamic schooling system.

Energy efficiency has become a critical focus in manufacturing plants due to rising operational costs and increasing environmental concerns. The growing importance of energy management is driven by the need to reduce energy consumption, lower emissions, and enhance overall operational efficiency. Traditional maintenance practices, such as reactive and preventive maintenance, often lead to unnecessary downtime, high repair costs, and inefficient energy usage. In contrast, predictive maintenance (PdM), supported by Internet of Things (IoT)-enabled sensor networks, offers a proactive approach to minimizing energy waste by predicting equipment failures before they occur. This study develops a predictive maintenance framework using IoT-based sensor networks to optimize energy usage and reduce energy losses in manufacturing plants. The research begins with an overview of IoT sensor network architectures and their applications in industrial automation, including sensors such as temperature, vibration, and pressure sensors. It explores predictive analytics techniques, such as machine learning and artificial intelligence, used for failure prediction, which are key to enhancing energy efficiency. The study emphasizes how predictive maintenance contributes to industrial sustainability by reducing carbon footprints and optimizing energy consumption. The research methodology involves the installation of IoT sensors in critical machinery, real-time data analysis using machine learning algorithms for failure prediction, and energy consumption measurement before and after implementing IoT-based interventions. The results show significant improvements in energy consumption efficiency and operational productivity. Predictive maintenance led to reduced unplanned downtime, increased equipment reliability, and a more sustainable manufacturing process. However, challenges such as sensor integration, initial setup costs, and data security concerns were identified. The study concludes with recommendations for integrating IoT-based predictive maintenance systems into manufacturing plants to further optimize energy usage and promote sustainability.

Islamic banking financing has become a crucial component of Indonesia's financial sector, providing a Sharia-compliant alternative to conventional financing. Despite its rapid growth, assessing the feasibility of Islamic banking financing remains a major challenge, particularly in terms of risk management, financial sustainability, and regulatory compliance. Previous studies have assessed financing feasibility using various methods, including the 5C approach (Character, Capacity, Capital, Collateral, and Conditions). However, research in this area remains fragmented, with a lack of systematic analysis of key trends, methodologies, and influencing factors. This study uses a Systematic Literature Review (SLR) to synthesize and analyze existing research on the feasibility of Islamic banking financing in Indonesia. The review covers studies published between 2020 and 2022, focusing on research distribution, analytical techniques, and key determinants affecting financing feasibility. The findings reveal that most studies emphasize credit risk assessment, financial literacy, and regulatory frameworks, but lack a unified approach to measuring feasibility. Furthermore, this study highlights gaps in the application of digital technologies, such as big data and machine learning, that can be used to strengthen the financing eligibility assessment system. The application of these technologies not only improves the accuracy of risk predictions but also enables Islamic banking institutions to reach more customers, particularly MSMEs and the informal sector, which have historically been underserved. The results of this study provide valuable insights for Islamic financial institutions, regulators, and researchers, highlighting the need for integrated risk assessment models, a better regulatory framework, and enhanced financial literacy initiatives to strengthen Islamic banking financing in Indonesia. This research contributes to the development of a more structured and comprehensive framework for evaluating financing eligibility, ensuring sustainable growth and financial inclusion in the Islamic banking sector.

The global clean water crisis is exacerbated by significant losses in water distribution networks (WDNs), resulting in inefficient use of both water and energy resources. Traditional methods of leak detection and pressure management often fail to address these inefficiencies, leading to substantial water wastage and high operational costs. This research aims to design a sustainable, smart water distribution system using advanced technologies such as Machine Learning (ML) for leak detection and automated pressure control. The system employs real-time monitoring through IoT sensors, which continuously gather data on water pressure, flow rates, and other critical parameters. This data is analyzed using various ML algorithms, including supervised and unsupervised learning models, to detect anomalies indicative of leaks. Additionally, the system integrates automated pressure control mechanisms that dynamically adjust pressure to prevent over-pressurization, reducing both water loss and energy consumption. By combining leak detection and pressure control, the proposed system offers a more efficient, sustainable solution to water resource management compared to traditional methods. The expected outcomes include a significant reduction in water loss, enhanced energy efficiency, and improved water service quality. However, the implementation of such a system in rural or small-town infrastructure faces challenges, including sensor maintenance, algorithm reliability, and regulatory issues. A cost-benefit analysis suggests that while the initial investment in smart technologies may be high, the long-term savings in water and energy costs outweigh these costs. This study underscores the potential of ML-based systems in enhancing water conservation, operational efficiency, and sustainability in water management.