Publication Search

Background: The rapid growth of warehouse automation and autonomous mobile robots has increased the need for adaptive navigation systems capable of operating safely and efficiently in dynamic industrial environments. Classical path planning algorithms such as A* and RRT perform well in structured settings but exhibit limitations when handling moving obstacles and environmental uncertainty. Objective: This study aims to develop and evaluate a reinforcement learning based navigation framework integrated with sensor fusion to improve path efficiency, collision avoidance, and robustness in dynamic warehouse scenarios. Method: An experimental research design was implemented combining high-fidelity simulation and real-world warehouse prototype testing. Deep Q-Network and Proximal Policy Optimization models were developed and trained using multi-sensor inputs from LiDAR, camera, and inertial measurement units. Performance was evaluated using path efficiency, collision rate, computational cost, and robustness metrics, with benchmarking against classical algorithms. Results: The results demonstrate that the Proximal Policy Optimization model achieved the highest path efficiency and lowest collision rate while maintaining stable computational performance under dynamic conditions. Reinforcement learning models significantly outperformed classical planners in adaptability and robustness, confirming their suitability for scalable industrial warehouse automation.

This study explores the development and evaluation of an adaptive Intrusion Detection and Response System (IDRS) driven by Reinforcement Learning (RL) for securing 5G networks. The RL-based IDS is designed to overcome the limitations of traditional security systems by dynamically learning from real time network traffic and adapting to emerging cyber threats. Introduction: The rapid growth of 5G networks, with their increased number of connected devices and complex traffic patterns, necessitates advanced security solutions that can detect and respond to evolving cyberattacks. Literature Review: Traditional Intrusion Detection Systems (IDS), including signature based and anomaly based methods, are not equipped to handle the dynamic nature of 5G networks, leading to high false positives and low detection accuracy. In contrast, RL offers significant improvements in adaptability, detection accuracy, and response time. Materials and Method: The study simulates 5G network traffic and develops an RL-based IDS using Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO) techniques. The performance of the RL-based system is compared to traditional IDS systems, focusing on detection accuracy, false positive rates, and response times. Results and Discussion: The RL-driven IDS demonstrated superior performance, achieving higher detection accuracy (95%) and faster response times (30 milliseconds) compared to traditional methods. However, challenges such as computational cost and model interpretability were identified. The study emphasizes the importance of adaptive learning mechanisms and the integration of RL into Zero Trust Architecture (ZTA) to enhance the security of 5G networks.

Cloud-based resource allocation and VM/container orchestration play a crucial role in ensuring performance, scalability, and energy efficiency in modern distributed computing environments. This study investigates the effectiveness of centralized and decentralized scheduling models combined with heuristic and optimization-based allocation strategies in container-based cloud infrastructures. A quantitative experimental approach was employed to evaluate system performance under varying workload intensities. Key evaluation metrics included response time, throughput, resource utilization, SLA violation rate, and energy consumption. The experimental results indicate that centralized scheduling mechanisms experience scalability limitations and increased latency under high workload conditions. Although optimization-based allocation improves performance within centralized architectures, coordination bottlenecks remain significant. In contrast, decentralized scheduling models demonstrate superior adaptability, reduced response time, and improved throughput due to distributed decision-making and reduced control overhead. The integration of intelligent optimization techniques further enhances resource utilization and energy efficiency, achieving the lowest SLA violation rates and highest system stability. Overall, the findings confirm that combining decentralized scheduling with optimization-driven resource allocation provides a more scalable and sustainable orchestration strategy for modern cloud environments. This approach is particularly suitable for dynamic, large-scale, and latency-sensitive applications in container-based and edge-integrated cloud systems.

The diversity in societal exercise preferences has increased significantly, with fitness emerging as a favored modern activity, particularly in urban areas of Indonesia. Fitness is valued for its effectiveness in restoring body fitness and achieving ideal body shapes swiftly. However, in the era of Industry 4.0, technological advancements have revolutionized the approach to fitness. Smartphone fitness applications have replaced the role of personal trainers by providing tailored exercise and dietary programs. User Interface (UI) plays a pivotal role in fitness applications, influencing User Experience (UX). The challenge lies in designing UI to accommodate user heterogeneity, both internally and externally. Adaptive UI emerges as a solution, capable of altering layout and content according to user characteristics. Kernwerk® Functional Fitness exemplifies a fitness application utilizing AI to optimize fitness routines. To enhance Kernwerk's UI adaptability, UX evaluation is conducted using UEQ+ modular extension, a comprehensive instrument for effectively and efficiently measuring user experience. Through this evaluation, components of UI and UX requiring further development to enhance Kernwerk's adaptability can be identified.

This research explores the preparedness of Indonesian cadets in multimodal transportation, focusing on 50 cadets from a transportation institution in Jakarta. Qualitative methods, including interviews and focus groups, were used to assess their knowledge, skills, and adaptability to emerging trends and technologies. The findings indicate that while cadets demonstrate a strong understanding of key concepts and principles, there are areas for improvement, particularly in problem-solving skills and adaptability to new technologies. Recommendations include enhancing problem-solving skills, incorporating training on emerging technologies, fostering collaboration and interdisciplinary learning, providing continuous professional development opportunities, strengthening industry-academia collaboration, evaluating and updating curriculum regularly, and promoting lifelong learning and professionalism. These recommendations aim to enhance the preparedness of Indonesian cadets and ensure that educational programs align with the evolving needs of the transportation industry.

This study explores the integration of hybrid AI control models, combining reinforcement learning (RL) and robust adaptive control, to improve the adaptability, performance, and stability of autonomous manufacturing systems. Traditional control systems, while effective under stable conditions, often struggle to cope with disturbances and varying production demands. Hybrid AI models, which integrate classical control methods such as Proportional Integral Derivative (PID) with machine learning techniques like RL, deep Q-networks (DQN), and deep deterministic policy gradient (DDPG), enhance decision-making capabilities in dynamic production environments. The study develops a hybrid RL robust control framework and tests it in both simulation and real-world scenarios. Performance metrics, including production efficiency, system stability, and adaptability, are assessed under various disturbance conditions, such as machine failures and fluctuating demands. The hybrid model significantly outperforms traditional PID control in terms of efficiency and stability, demonstrating faster convergence and better adaptability in dynamic environments. Statistical analysis confirms the superiority of the hybrid system over standalone RL models and traditional PID control. This model’s scalability and adaptability make it a promising solution for Industry 4.0 applications, addressing key challenges in real-world manufacturing systems by ensuring computational efficiency and the ability to manage large-scale data. The findings contribute to the development of more robust and efficient control strategies for autonomous manufacturing systems in uncertain environments.

This study focuses on developing a global curriculum model that integrates intercultural and multilingual competencies to enhance students’ academic and communicative skills. The proposed framework emphasizes flexibility, inclusivity, and adaptability, combining theoretical knowledge with practical applications to help students thrive in multicultural, multilingual, and digitally mediated global contexts. Using a qualitative curriculum design approach, the study examines the integration of intercultural competence and multilingual education into existing curricula, offering a model adaptable to diverse educational settings. It further explores the impact of this curriculum on students' ability to communicate across cultural and linguistic boundaries, highlighting the importance of digital literacy and global communication skills. The findings indicate that the intercultural model enhances students' academic performance and global citizenship, preparing them for international collaborations and addressing global challenges. Additionally, the curriculum's adaptability ensures its alignment with digital education demands, making it relevant in today’s evolving educational landscape. The research underscores the importance of curricula that embrace cultural diversity and linguistic multiplicity, promoting inclusivity and preparing students for the complexities of an interconnected world. The study concludes with practical recommendations for educators, policymakers, and curriculum developers to implement intercultural and multilingual frameworks globally, ensuring students are equipped with the necessary skills for success in the digital and globalized world.

Al-Hamidiyah Depok Islamic Foundation is one of the educational institutions that uses YouTube social media as a medium for disseminating information. The NGASUH (Ngaji Bersama Pengasuh) program premiered on March 14, 2022 until this thesis was made, it has reached 49 episodes. The obstacles faced such as technical constraints and the host cannot attend live broadcasts. This research aims to find out the process of making the NGASUH program through the YouTube social media of the Al-Hamidiyah Islamic Foundation as a means of disseminating Islamic information for students, teachers, employees at the Al-Hamidiyah Islamic Foundation and to find out what obstacles were faced during the process of making the NGASUH program through the YouTube social media of the Al-Hamidiyah Islamic Foundation. The research theory in this study is production theory which consists of pre-production, production, and post-production. This research methodology uses a qualitative approach with descriptive methods with data collection techniques are in-depth interviews. The pre-production of the NGASUH program is the initial stage in the event production process which involves planning, preparing, and organizing all the necessary aspects before the live broadcast is carried out. The production stage of a live program requires tight coordination, adaptability, and readiness to handle situations that may arise during the broadcast. The entire production team must work together to ensure the smooth running of the event and provide a good experience to the audience. The post-production phase of a live program is the phase after the live broadcast is completed, where the evaluation, processing, and distribution of the broadcast results are carried out. This stage is important to evaluate the quality of the broadcast, collect feedback, and conduct follow-ups based on the results of the broadcast such as storing the broadcast materials properly for future reference and archives.

This study examines the influence of international mobility programs on the development of intercultural competency in university students. Through a mixed-methods approach, data was collected from participants across several mobility programs to understand changes in attitudes, awareness, and skills relevant to intercultural communication. Findings indicate that students with international exposure show higher adaptability, cultural sensitivity, and openness compared to their peers. The research suggests that well-structured mobility experiences can significantly enhance students' readiness to work in global settings.

Artificial Intelligence (AI)-based Decision Support Systems (DSS) have become a central component of digital transformation initiatives across various industries. While prior studies have primarily emphasized technical aspects such as accuracy, performance, and computational efficiency, less attention has been given to the integration of human-centered principles and scalable architectural design. This study aims to examine how AI-based DSS can be enhanced through the combined application of Human-Centered Artificial Intelligence (HCAI) principles and scalable AI architecture. Using a qualitative, literature-based research methodology, this study systematically analyzes peer-reviewed publications indexed in Scopus to identify key dimensions influencing the effectiveness and sustainability of AI-driven DSS. The findings indicate that technical capabilities alone are insufficient to ensure successful adoption and long term impact. Instead, transparency, explainability, ethical governance, and user empowerment core elements of HCAI are critical for fostering trust and user acceptance. Furthermore, scalable architectural principles, including modularity, interoperability, and adaptability, are essential for enabling AI-based DSS to operate reliably in large-scale and dynamic environments. This study contributes a unified conceptual framework that bridges technical scalability and human-centered design, offering theoretical insights and practical guidance for developing trustworthy, scalable, and sustainable AI-based Decision Support Systems in digital transformation contexts.

This study evaluates the role of instructional leadership in fostering inclusive education practices within primary schools. The research investigates how principals, through their leadership practices, contribute to the development of a culture of inclusion, particularly for students with special needs. A mixed-method approach was employed, combining quantitative surveys of primary school teachers and qualitative interviews with principals and educators. The findings reveal that effective instructional leadership plays a crucial role in enhancing teacher engagement and promoting inclusive practices. Key leadership practices such as clear communication, ongoing support, and the active promotion of inclusivity were found to significantly impact the success of inclusive education. Additionally, the study highlights the importance of leadership training, with principals who received formal training being more capable of supporting inclusive practices. The involvement of the school community, including teachers, parents, and local stakeholders, was also identified as a critical factor in sustaining inclusive education practices. Finally, the study emphasizes the need for curriculum flexibility, showing that the ability to adapt teaching methods and materials to meet the diverse needs of students is vital for fostering inclusion. These findings underline the importance of comprehensive leadership development, community collaboration, and curriculum adaptability in creating inclusive primary school environments.

In the era of technology 4.0, Indonesia is pursuing progress through the adoption of smart contracts on the blockchain. The government responded to this by establishing technology regulations to address emerging challenges. Legal principles demonstrate their adaptability in the digital era by utilizing information technology to build a modern legal and administrative framework, in line with the vision of industrial development 4.0. This normative juridical legal research evaluates the application of legal norms in a concrete context, using statutory and conceptual approaches. Data collection was carried out through literature study using primary, secondary and tertiary legal materials. Data analysis uses qualitative descriptive methods. Smart contracts are increasingly widely used, especially in electronic transactions such as stock trading, crypto and hotel reservations. As a form of electronic agreement, smart contracts facilitate the automation of contract processes. However, its use must comply with the law and technology neutral principles in the ITE Law. Even though it is automatic, this technology is recognized as an Electronic Agent in accordance with Article 1 Number 8 of the ITE Law. The validity of these automated contracts is only questioned if it is proven that the automated system is problematic. Smart contracts in Indonesia are recognized in the context of contract law based on freedom of contract and the legal basis of the Civil Code. This recognition occurs because the Civil Code is open and complementary. However, the use of smart contracts must comply with statutory regulations, principles of decency and public order. Regulations governing smart contracts include the ITE Law, PP PTSE, and PP PMSE. These three regulations stipulate the procedures for using electronic contracts, providing a clear legal basis for the implementation of smart contracts.

Micro, Small and Medium Enterprises (MSMEs) have a vital role in the Indonesian economy, creating new jobs, innovation and unique strategies. The growth phenomenon of MSMEs presents challenges and opportunities, encouraging the need for targeted strategies, in-depth market understanding and adaptability. This research explores strategic management practices in MSMEs in Dee Lestari's "Rantai Tak Putus". The strategies implemented include internal development, making the right decisions, and consistency in implementing positive values. The MSME players in this book are able to adapt strategic management to their business needs, not only for immediate business growth, but also to build a solid foundation for long-term sustainability. This creates an environment that supports business growth, strengthens competitiveness, and ensures the adaptability of MSMEs to change for sustainable business continuity.

This research delves into the psychological features of seamen's activity during emergency situations as perceived by 240 cadets in their third semester at the Maritime Institute Jakarta (STIP Jakarta). The study employs a qualitative descriptive approach to unravel the cognitive, emotional, and behavioural responses exhibited by cadets in simulated emergency scenarios. The findings underscore the transformative journey of cadets, transitioning from initial stress and anxiety to a controlled sense of urgency, showcasing the efficacy of the institution's training methodologies. A significant aspect of this research is the examination of the correlation between language proficiency, particularly in English, and effective emergency communication. Cadets recognise English as a shared language that enhances communication efficiency during emergencies. The study reveals the pivotal role of linguistic skills in coordinating actions seamlessly, highlighting the practical implications of language proficiency in emergency management within the global maritime context. The implications for maritime education are profound, emphasising the need for a holistic approach that integrates psychological preparedness and targeted language development initiatives. The research recommends continuous professional development, global collaboration among maritime institutions, and industry partnerships to ensure the adaptability and relevance of education to evolving industry standards. In conclusion, this research contributes valuable insights to the discourse on maritime education, emphasising the importance of cultivating a well-rounded skill set among cadets. The findings inform curriculum development, training methodologies, and strategies to enhance the psychological resilience and linguistic proficiency of future seafaring professionals, positioning them as adept and globally competent officers.

This qualitative research aims to explore the role of Strategic Financial Fluency (SFF) as a catalyst for growth in Micro, Small, and Medium Enterprises (MSMEs). The study employs a multi-method approach integrating literature review, case studies, and expert interviews to construct a comprehensive understanding of SFF and its impact on MSMEs' growth trajectories. Sampling techniques involve purposive sampling of MSMEs representing diverse industries and geographical locations to ensure comprehensive data collection. Data analysis employs thematic analysis, focusing on identifying patterns and themes related to SFF adoption, utilization, and its influence on business growth. The findings reveal that MSMEs equipped with Strategic Financial Fluency demonstrate higher adaptability, resilience, and growth potential. Moreover, SFF facilitates informed decision-making, efficient resource allocation, and strategic planning, thus fostering sustainable growth in MSMEs. This research contributes to the existing literature by highlighting the pivotal role of financial literacy and strategic financial management in enhancing the competitiveness and growth prospects of MSMEs in a dynamic business environment.

First year university students would experience a transition period from high school to college. This transition period was a challenge experienced by new students. Several aspects that were influential in overcoming these challenges include achievement motivation, adaptability, and self-efficacy. The aim of this research was to determine the description of achievement motivation, self-efficacy and adaptability in First Semester Students of D3 Keperawatan Politeknik Negeri Indramayu. This research was a descriptive observational study, with the research subjects was 1st semester of D3 Keperawatan Politeknik Negeri Indramayu, totaling 94 students. Data collection techniques in the research used the Achievement Motivation Scale, Self-Efficacy Scale, and Adaptation Ability Scale. The research results showed that the level of achievement motivation, adaptability, and self-efficacy of 1st semester of D3 Keperawatan Politeknik Negeri Indramayu is quite adequate.

Employee adaptability skills are increasingly important in a rapidly changing business environment. A recent literature review reveals the evolution of employees' adaptability skills during the COVID-19 pandemic and efforts to strengthen them. Factors such as leadership, changes in the work environment, and organizational support influence changes in adaptability. Inclusive leadership, open communication and social support form key elements in this strategy. This article describes the development of employee adaptability skills in the context of external change, especially the COVID-19 pandemic. This article describes material for developing employee adaptability skills which includes understanding the concept of adaptability, adaptability development strategies, and the benefits for companies and employees. This material is designed to help employees develop their abilities to deal with change, increase resilience, manage stress and innovate. By investing time and resources in developing adaptability skills, organizations can increase their competitiveness and employees can achieve success in a dynamic work environment. The results of this literature review provide useful insights for organizations that wish to prioritize developing employee adaptability in response to increasingly complex business dynamics.

The main objective of this research is to determine the direct influence of career adaptability and perceived organizational support on employee performance. The population and sample in this study were 120 permanent employees of the Royal Prima Medan Hospital. This type of research is quantitative. Data was obtained from distributing questionnaires. Data analysis uses Smart Pls, where it is hoped that the results of this research will be able to predict employee performance. The research results show that career adaptability and perceived organizational support directly affect employee performance. Then, perceived organizational support is assessed as the most dominant variable in influencing employee performance.

In the ever-evolving digital era, disruption challenges face Micro, Small, and Medium Enterprises (MSMEs), including STIE Ganesha students who are preparing to enter the business world. This research explores management strategies that can help MSMEs face disruption in the digital era. Using a qualitative approach, this research aims to identify disruption trends, challenges faced, and effective management strategies. The research was conducted over six months, involving in-depth interviews with MSME owners who have experienced digital disruption. Data analysis used a qualitative approach by formulating patterns of findings that emerged from the interviews. The results showed that the strategy of STIE Ganesha students in facing disruption is the adoption of MSME digital technology, understanding of data and analytics, continuous innovation, focus on customer experience, collaboration and partnerships, increasing cyber security, increasing human resource capacity, flexibility and adaptability of creative marketing understanding of business legal aspects. The implication of this research is to provide practical guidance for STIE Ganesha students who will later run or support MSMEs. Research limitations include limitations in the number of samples and focus on local cases.

The low quality of public services is still a classic problem in Indonesia. Therefore, it is time for the government to implement e-government as an effort to improve services to the community. This research aims to determine the effectiveness of making online SKCK at MPP Pandeglang Regency as an implementation of e-government and to determine the factors that support and hinder e-government at MPP Pandeglang Regency. The research uses a qualitative method with a descriptive approach, a case study of making online SKCK at the Pandeglang Regency MPP. This research found that the effectiveness of e-government as seen from the indicators of productivity, adaptability, job satisfaction and general development is good. The supporting factor is the availability of adequate facilities and infrastructure. Meanwhile, the inhibiting factors are the lack of human resources and inappropriate placement of officers. This research has the implication that the e-government services provided should be socialized first so that they can be implemented optimally in society.