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The integration of blockchain technology with Multi-Agent Reinforcement Learning (MARL) presents a promising solution for optimizing resource allocation and ensuring security in decentralized network environments, particularly in 5G and 6G network slicing. This research proposes a model that combines the security features of blockchain with the adaptive, decentralized decision-making capabilities of MARL. Blockchain ensures the integrity and transparency of resource allocation by providing a secure, tamper-proof ledger for transaction validation, while MARL allows agents to dynamically allocate resources based on real-time network conditions. The simulation results demonstrate significant improvements in resource allocation efficiency, fairness among users, and resilience to cyberattacks. By combining these two technologies, the proposed model overcomes many of the challenges posed by traditional centralized systems and offers an enhanced, secure, and fair solution for resource distribution in future mobile networks. However, scalability remains a challenge, especially in large-scale networks where transaction processing and consensus overhead can create bottlenecks. Additionally, training complexity in MARL models presents computational challenges, particularly in highly dynamic network environments. The model's performance trade-offs, including the balance between high security and system overhead, are also discussed. Future research should focus on optimizing blockchain consensus mechanisms to improve scalability and enhancing MARL model training techniques to reduce computational costs and improve real-time decision-making. This integration holds significant potential for revolutionizing resource allocation in 5G and 6G networks, enabling more efficient, secure, and fair management of network resources in the increasingly complex and decentralized digital ecosystem

The development of the internet in Indonesia has opened up numerous opportunities, including in the field of online commerce. One widely used feature in online transactions is the "Paylater" system, as implemented by Shopee through its Shopee Paylater service. This feature allows users to purchase goods now and pay for them later, with relatively low interest rates. This study aims to examine the regulations and implementation of Shopee Paylater, as well as the legal protection available to consumers in cases of default or issues with the service. The study refers to the Indonesian Civil Code, Law No. 8 of 1999 on Consumer Protection, and the Financial Services Authority Regulation (POJK) No. 77/POJK.01/2016 on Information Technology-Based Lending Services. The research findings indicate that Shopee Paylater users are bound by a standard agreement with PT. Commerce Finance during the purchasing process. Shopee is responsible for protecting consumers in accordance with applicable regulations, but breaches related to network security can pose risks to consumers. In addition, while the service facilitates easier access to goods and services for users, it is crucial that consumers fully understand the terms and conditions of the service, including the consequences of late payments. The study also emphasizes the need for clearer and more comprehensive consumer protection regulations, especially in light of the rapid growth of digital financial services. This research highlights the importance of adequate legal protection for users of Paylater services to ensure their rights are safeguarded in the evolving digital economy.

In the digital era, the internet has become a primary necessity for people in both urban and rural areas, driving the development of wireless networks such as Wireless Mesh Networks (WMN) that connect nodes in a multi-hop, self-organizing manner. WMNs offer advantages including flexibility, resilience, automatic configuration, self-healing capabilities, and cost efficiency, making them suitable for various sectors, including industry, residential areas, offices, and education. This research employs a qualitative approach through literature review on wireless networks and Mesh topology. Descriptive analysis is conducted to evaluate the strengths, weaknesses, and operational mechanisms of Mesh topology. The findings indicate that implementing Mesh topology in wireless networks provides reliable, flexible, and fault-tolerant connectivity, as each node can function as both a router and a data transmitter/receiver. Although installation is complex and requires numerous cables or ports, Mesh topology remains an effective solution to the limitations of conventional wired and wireless networks. Its advantages in redundancy, security, and scalability make Mesh topology a viable primary choice for the development of modern networks.

The SENABUNG Serang Volunteer Community has various humanitarian programs to help the poor, street children, and other communities in need. This study aims to determine the communication strategy of the SENABUNG Serang Volunteer Community in increasing its presence in the community, as well as to analyze the obstacles faced. The research method uses a descriptive qualitative approach with the Resource Mobilization theory. Data were obtained through interviews, observation, and documentation. Data validity techniques use source triangulation to ensure the validity of the research findings. The results show that the existence of the SENABUNG community is built through the mobilization of five types of resources, namely human, material, organizational, socio-cultural, and moral resources. The community has succeeded in mobilizing volunteers, collecting donations, building social networks, and gaining moral legitimacy from the community. However, this study also found internal obstacles such as limited volunteers and time, inadequate equipment, unstable morale and transportation facilities, as well as external obstacles such as dependence on donations and digital security threats. Despite these successes, the study highlights significant challenges. Internally, the community struggles with a limited number of volunteers, which affects the sustainability of its programs. Moreover, the volunteers' time commitment is often restricted, limiting their capacity to engage fully. Additionally, inadequate equipment and unstable morale present further hurdles. Externally, the community's reliance on donations for funding leaves it vulnerable to fluctuations in contributions, and digital security threats pose risks to the integrity of the information shared across platforms.

The UNS Community Service Program (KKN) Batch 68 was conducted from July to August 2025 in Jaten Village, Karanganyar Regency, Central Java. This program focused on educating the community about the utilization of organic waste, particularly dragon fruit (Hylocereus spp.) peel, which is generally underutilized. Dragon fruit peel has the potential to be developed into functional food products as it contains fiber, vitamins, and pectin. Through the “Dragon Fruit Peel Waste Management into Sauce” workshop, participants were provided with knowledge and skills to process organic waste into value-added products while supporting household food security. The implementation methods included counseling, demonstrations, and hands-on practice. The results showed an increase in community understanding of food waste management, improved skills in processing dragon fruit peel into sauce, and the establishment of communication networks among village cadres for program sustainability. This innovation also holds potential to be developed into micro-enterprises in the healthy food sector.

Wireless Medical Sensor Networks (WMSNs) are a key component of modern Healthcare Internet of Things (IoT) systems, enabling continuous and real-time monitoring of patients’ physiological parameters. These networks support timely medical intervention, improve patient outcomes, and facilitate remote healthcare delivery. However, due to the open and resource-constrained nature of WMSNs, they are highly susceptible to various security threats, particularly during the authentication phase. Existing authentication protocols have been found vulnerable to a range of attacks, including impersonation, session key disclosure, and gateway database compromise, which can lead to severe privacy breaches and potentially life-threatening situations. To address these issues, this paper proposes a secure and lightweight three-factor authentication protocol tailored for WMSNs in healthcare IoT environments. The proposed protocol integrates Elliptic Curve Cryptography (ECC) for strong public key-based security with minimal computational overhead, fuzzy extractors to securely handle biometric information and ensure resistance against biometric template compromise, and session-based randomness to achieve forward secrecy and prevent replay or key-compromise impersonation attacks. Security analysis demonstrates that the proposed protocol successfully mitigates prominent threats such as impersonation attacks, man-in-the-middle attacks, session key leakage, and database compromise. In addition, the protocol ensures mutual authentication between the user, the gateway, and the sensor nodes, while maintaining data confidentiality and integrity. Performance evaluation indicates that the protocol offers significantly reduced computational cost and communication delay compared to existing schemes. Its low energy consumption and minimal storage requirements make it suitable for deployment in resource-constrained medical devices and large-scale IoT healthcare networks. The results highlight the protocol’s scalability, energy efficiency, and robustness, making it a practical and secure solution for safeguarding patient data and ensuring trustworthy communication in WMSNs-based healthcare IoT systems.

The development of information and communication technology (ICT), particularly the use of Artificial Intelligence (AI), the Internet of Things (IoT), and big data, has transformed Indonesia's national security threat landscape. Threats that previously focused on traditional military aspects have now shifted to non-traditional cyber threats, such as cyberattacks, digital espionage, and infrastructure sabotage. According to PROXSIS IT GRC data, in 2024, more than 19 million cyberattacks were recorded against websites in Indonesia. While this figure is a decrease compared to the previous year, this trend is thought to reflect a shift towards more structured and organized tactics by threat actors. In response, the Indonesian government established the National Cybersecurity Action Plan 2024–2028 as a strategic guideline. Furthermore, cyber diplomacy is being promoted through bilateral and multilateral cooperation, for example through the signing of memorandums of understanding (MoUs) with the UK and Kaspersky. This cooperation includes the exchange of intelligence information, strengthening human resource capacity, raising public awareness regarding cybersecurity, and protecting critical information infrastructure. This study uses non-traditional security theory and defense diplomacy to analyze the strategies, challenges, and prospects of Indonesia's cyber policy. The analysis demonstrates that cyber defense diplomacy plays a crucial role as an instrument for integrating technology, regulation, and international collaboration in safeguarding digital sovereignty. In addition to strengthening threat detection and mitigation capabilities, this diplomacy also builds networks of trust with partner nations, which is essential amidst the increasing complexity of global threats. Therefore, in the era of digital globalization, full of interconnections, cyber defense diplomacy serves not only as a national protection tool but also as Indonesia's contribution to global cybersecurity stability. This effort prioritizes synergy between technological innovation, law enforcement, and sustainable international cooperation.

This study compares the performance of two deep learning models, namely Convolutional Long Short-Term Memory (ConvLSTM) and Long-term Recurrent Convolutional Network (LRCN), in the task of recognizing human activity from videos. Human activity recognition is an important field in computer vision with many applications, such as security monitoring, human-computer interaction, and social media-based video analysis. ConvLSTM is a model that combines convolution operations with long-term memory LSTM, thus capable of capturing spatial and temporal information simultaneously. This approach is ideal for processing video data sequences that have spatial and temporal dimensions. On the other hand, LRCN combines the power of spatial feature extraction from Convolutional Neural Network (CNN) and temporal sequence modeling through Recurrent Neural Network (RNN), specifically LSTM, to understand movement patterns in videos. The study used the UCF50 dataset consisting of 50 activity classes, but was limited to five classes for the focus of the experiment. The dataset was divided into 80% for training and 20% for testing, and the model was drilled for 50 epochs using early stopping to prevent overfitting. The results show that both models have high training performance. ConvLSTM achieved a training accuracy of around 98% and a validation accuracy of 90%, while LRCN achieved a training accuracy of 99.5% and a validation accuracy of 88%. Although ConvLSTM demonstrated good stability on the validation data, further testing using TikTok videos as real-world data showed that LRCN had a higher confidence level in recognizing activities, with most predictions achieving confidence scores above 80%. This difference in performance indicates that while ConvLSTM excels in generalizing on training data, LRCN is more robust to real-world data variations.

Money laundering is a serious crime that has a significant impact on economic and social stability, as well as the integrity of the financial system. This crime is often associated with serious crimes such as corruption, narcotics, and terrorism. Money laundering poses a major threat to national security, conceals the origin of illicit funds, and undermines a healthy economic system. To combat this crime, Indonesia has imposed criminal sanctions based on Law Number 8 of 2010, which aims to provide a deterrent effect on perpetrators and prevent similar crimes from occurring in the future. However, the effectiveness of these criminal sanctions remains a critical challenge, given the various difficulties in their enforcement, such as the complexity of tracking the flow of funds, limited law enforcement resources, and the increasingly sophisticated modus operandi of perpetrators who often work together with international networks. This study seeks to examine the effectiveness of criminal sanctions in combating money laundering and identify obstacles in their implementation. The research method used is juridical-normative research with a legal regulatory framework. Primary data was obtained through literature review and examination of legal documents, while secondary data came from relevant literature, reports, and academic studies. The urgency of this research stems from the importance of evaluating and strengthening the application of criminal sanctions to protect the national financial system from the risk of money laundering. Without concrete steps to increase the effectiveness of sanctions, money laundering crimes will continue to proliferate and pose a threat to the national economy, weaken the legal system, and erode public trust in efforts to combat economic crime.

Blockchain logistics represents the integration of blockchain technology into the logistics sector, aiming to enhance efficiency, transparency, and security across supply chain processes. From an Islamic economics perspective, digital transformation must align with core values such as justice, transparency, and honesty to support the development of fair and sustainable logistics systems. The decentralized nature of blockchain offers promising solutions for building supply chains rooted in Islamic ethical principles. This study conducts a bibliometric analysis to examine the development and research trends of blockchain logistics within the context of Islamic economics. Using VOSviewer software, relevant scientific publications were analyzed based on bibliographic data sourced from reputable academic databases. Bibliometric parameters—such as the maximum number of authors per document and the minimum number of documents per author—were applied to identify key contributors and dominant research themes. The bibliometric mapping reveals the growth trajectory of blockchain logistics research framed by Islamic values. The visualization highlights research clusters, prominent authors, co-authorship networks, and publication trends that illustrate the evolution and scholarly interest in this interdisciplinary area. Emerging themes suggest a convergence between blockchain-driven logistics innovation and ethical economic practices advocated in Islamic teachings. The findings provide a comprehensive overview of the current landscape and collaboration opportunities in blockchain logistics research through an Islamic lens. This study contributes to the strategic positioning of future research by identifying gaps, potential synergies, and critical areas for development. Ultimately, it offers a foundational reference for scholars seeking to explore the integration of Islamic ethical principles within the advancement of blockchain-enabled logistics systems.

The increasing vulnerabilities of modern enterprise network security systems highlight the necessity of adopting a more comprehensive and adaptive security approach than traditional VPN infrastructures. This study explores the design and implementation of Zero Trust Network Access (ZTNA) using the Cloudflare platform at PT FHI, focusing on addressing the weaknesses caused by uncontrolled remote access and legacy security models. The research adopts an experimental methodology based on the Network Development Life Cycle (NDLC), which includes systematic phases such as needs analysis, architectural design, system implementation, testing, and performance evaluation. Data were collected through structured interviews with IT managers and security specialists, direct observation of network logs, and comprehensive testing involving three different categories of end users. The findings demonstrate significant improvements in role-based access control, granular authentication, and the elimination of unrestricted access to internal resources. Additionally, real-time monitoring and alerting features available through the Cloudflare dashboard enhance visibility and responsiveness to potential threats. The implemented system successfully applies the “never trust, always verify” principle by blocking unauthorized access attempts, enforcing continuous validation, and producing detailed audit logs. Performance evaluation results confirm stable connections, acceptable latency for critical business applications, and an overall improvement in network security posture while maintaining operational productivity across departments..

Growth rapid computing cloud, especially on academic, government, and service platforms. public, has trigger improvement frequency and complexity Distributed Denial of Service (DDoS) attacks. Intelligent DDoS attacks AI based capable copy pattern Then cross user valid, so that difficult detected and mitigated. The majority approach mitigation moment This nature reactive, no scalable, and tends to sacrifice availability service for authorized users. Research​ This aiming develop architecture proactive and adaptive defense​ For ensure continuity service during attack ongoing. Security model proposed hybrid​ integrating Zero Trust Architecture (ZTA), adaptive bandwidth control, and isolation service container -based. Architecture consists of from three layer Main: (1) ZTA Policy Engine which performs verification identity and assessment behavior through tokens and policies intelligent; (2) Adaptive Bandwidth Load Balancer which automatically dynamic separate and arrange Then cross based on reputation and level trust ; and (3) Containerized Service Cluster which groups request to in different containers For user trusted and not known . Components addition such as blockchain -based smart contracts are used For recording request and verification access , as well as lightweight AI module used for profiling then cross in real-time. Simulation results show that this model succeed increase availability service for user trusted during attack , press false positive rate , as well as optimize allocation source power. Integration of zero trust policies with intelligence Then cross and segmentation service in real-time forming framework effective and scalable defense​ to modern DDoS threats . In conclusion , the study This contributes a robust , adaptive , and modular architectural model for maintain continuity cloud services in condition network at risk .

The development of digital technology today has influenced various aspects of human life, from communication to instant access to information, but the digital literacy gap is still felt by some people, especially in non-technical communities. This community service activity aims to improve basic understanding of computers and the internet for the Purwokerto Fixie Community, a bicycle community whose members come from various ages and educational backgrounds. The socialization method is carried out interactively with a simple language approach, so that the material can be optimally absorbed by participants who have minimal digital experience. The material presented includes an introduction to computer devices, basic concepts of internet networks, digital security, and an understanding of the latest technologies such as 5G and the Internet of Things (IoT). The evaluation results showed an increase in participants' knowledge of basic digital literacy, as well as an awareness of the importance of using information technology safely and responsibly. This activity is the first step in efforts to empower communities through increasing inclusive and applicable digital literacy.

This study examines collaborative implementation strategies as an effective model for addressing employment challenges in the era of economic and technological transformation. Focusing on collaboration among the state, business sector, and labor unions, the study adopts a qualitative-descriptive approach through literature review, policy analysis, and case studies. Findings reveal that trilateral partnerships—inspired by the European concept of flexicurity—promote enhanced job security, worker productivity, and adaptability. The empowerment of labor unions through collective agreements and mediation has proven to strengthen industrial dialogue and prevent conflict. In Australia’s public sector, consultative committees involving union delegates and management demonstrate the effectiveness of consensus-based policymaking. Strategic recommendations include strengthening dialogic capacities, process digitalization, and the application of worker-driven social responsibility (WDSR) models for platform-based employment. The study concludes that multistakeholder collaborative networks are key to reinforcing labor market resilience and advancing social justice.

To securely access servers remotely, an important protocol in the modern era is Secure Shell (SSH). However, brute force attacks, which are automated attempts to guess repeated username and password combinations, are often the main target of this service. The purpose of this research is to evaluate the vulnerability of SSH services to brute force attacks and evaluate how effective Fail2Ban is as a mitigation tool. This method uses simulated experiments with two virtual machines; Kali Linux is used as the attacker with the Hydra tool and Ubuntu Server is used as the target. The results show that SSH is highly vulnerable to brute force attacks if not protected. Hundreds of login failures from the same IP without restrictions show this. After using Fail2Ban, the system can automatically find and block the attacker IP after three unsuccessful logins. With easy configuration and fast threat detection, Fail2Ban has been proven to improve the security of SSH services. This study suggests using Fail2Ban to improve the defense of SSH services against cyberattacks, especially brute force attacks.

The use of WiFi networks at home has become an essential need in the digital era, but many people still do not understand how to use it optimally and safely. This socialization activity aims to improve digital literacy, especially in managing household WiFi networks, for teenagers who are members of youth organizations in Darmakradenan Village, Karangpucung. The methods   used include presentations, interactive discussions, and distribution of educational modules. The results of the activity showed an increase in participants' understanding of basic network security steps, signal management, and awareness of their role as information technology agents. This activity is expected to contribute to creating a safer and more productive digital ecosystem at the community level.

Abstract. The background to this research is that the trend of non-cash or cashless transactions is increasingly widespread in Indonesia. The Bank is also trying to expand its network sector by providing a number of conveniences when carrying out financial transactions without the need to come to the bank. One of them is transactions via smartphone or M-Banking. However, behind the development of banking and the ease of making transactions via M- Banking, there is also the risk of cyber-based crime or threats, so this research aims to analyze the security of transactions when using M-Banking services. The focus of this research is: 1) What is the security of transactions when using M-Banking services at Bank Muamalat Indonesia Denpasar Branch Office? 2.) What are the efforts to increase security for customers who make transactions via M-Banking services at Bank Muamalat Indonesia Denpasar Branch Office? The objectives of this research are: 1) To find out the security of transactions when using M-Banking services at Bank Muamalat Indonesia Denpasar Branch Office. 2) To find out how efforts to increase transaction security are carried out by Bank Muamalat Indonesia Denpasar Branch Office. The research method that will be used is descriptive qualitative, with data collection techniques through observation, interviews and documentation, as well as data validity techniques through the triangulation method. The research results will be presented in a descriptive manner. The result of this research is that transaction security in M-Banking services carries out risk analysis to detect threats that occur. 1) risks in using M-Banking services can be detected through the risk analysis process carried out by the bank, which includes identification, evaluation and risk assessment, as well as risk management. 2) the improvement efforts made are by managing customer information security in accordance with CIA standards (Confidentiality, Integrity, Availability) so that customers can use M-Banking services safely and comfortably.

The rapid use of the internet in public spaces increases the need for free connectivity, such as public Wi-Fi. However, the low digital literacy of the community makes them vulnerable to various cyber attacks such as data theft, malware distribution, and man-in-the-middle attacks. This study aims to analyze the effectiveness of socialization activities as a means of increasing awareness of network security in rural communities. The activities were carried out in Darmakradenan Village, Grumbul Karangpucung using a participatory method based on direct education. The results showed an increase in public understanding of public network threats and preventive measures such as the use of VPNs and network security verification. This study shows that community-based socialization is effective in building a safe and wise digital culture at the local level.

This study explores the development and application of a digital twin-driven cybersecurity risk assessment model for Industrial Internet of Things (IIoT) networks. The increasing complexity and interconnectivity of IIoT systems have expanded the attack surface, making them vulnerable to a wide range of cyber threats. The digital twin model addresses this challenge by creating real-time virtual replicas of physical systems, which can simulate and predict network vulnerabilities and attack vectors. The model uses machine learning algorithms and real-time data to simulate cyberattacks, including Distributed Denial of Service (DDoS), malware, and data breaches. By providing continuous monitoring and dynamic risk predictions, the digital twin model enhances the resilience of IIoT networks compared to traditional cybersecurity frameworks. The findings indicate that the model's ability to predict potential cyber threats and simulate various attack scenarios provides a more proactive and accurate approach to cybersecurity in IIoT environments. Additionally, the study highlights key mitigation strategies, including adaptive security mechanisms, real-time anomaly detection, and the use of lightweight encryption for resource-constrained devices. Despite its effectiveness, challenges such as computational requirements, integration with legacy systems, and scalability were identified. This research underscores the strategic importance of digital twin models in securing IIoT systems and advancing Manufacturing 4.0 ecosystems. Future research should focus on enhancing model accuracy, expanding its application to diverse industrial sectors, and improving interoperability with legacy systems to further strengthen the security posture of IIoT networks.

This study aims to explain the strength of social capital owned by Nurdin in political contestation in 2016. This type of research is a descriptive qualitative study to explore the strength of social capital in the transformation of village head leadership. Meanwhile, the approach used is the phenomenological approach The results of this study indicate that the previous leadership style that the author limits only captures the leadership style for the period 2002-2009. During the 2002-2004 period, when Karaeng Oddang was in charge, in his leadership he tried to be more democratic, but the domination of his father (Karaeng Manna) was still strong at that time. Likewise with Aji Awaluddin 's karaeng leadership style, he was a typical leader who was considered by the community to be very good and realized democratic values ​​during his tenure as head of Kindang village for the 2004-2009 period. In 2009-2016, this was where leadership transformation took place. Photographing Nurdin's leadership style for the period of 2009 cannot be separated from appreciation and praise. However, this criticism did not have an impact on the 2016 village head election. Nurdin won the pilkades again.  Nurdin's strength of social capital in the election has won him victory. The rise of primordial sentiment among ordinary people (tumaradeka) as Nurdin's strength, and on the other hand the rise of negative stereotypes against karaeng that spread to the issue of group identity and the strong strength of social networking capital, bonding, bridging and linking greatly colored the 2016 pilakdes. Social capital security control is a selling point for Nurdin so that he can get support from the community compared to other candidates who are deemed unfit and unable to anticipate security in Kindang village.