Publication Search

The advancement of digital technology has created new opportunities for cybercrime, including revenge porn the non-consensual distribution of intimate content motivated by revenge. In Indonesia, such cases have surged significantly, predominantly affecting women of productive age, with multidimensional consequences including psychological trauma, social stigmatization, and job loss. This study analyzes the element 'without right' (tanpa hak) in Article 27 paragraph (1) of the Electronic Information and Transactions Law (UU ITE), which is both the core and the main source of legal uncertainty in prosecuting revenge porn cases. Through normative legal research using statute and case approaches, analyzing the Banten High Court Decision No. 96/Pid.Sus/2023/PT BTN, this research finds that the element 'without right' must be interpreted holistically by making a clear distinction between consent to create and consent to distribute. The appellate court decision demonstrates a progressive human rights-based approach, integrating the principle of reasonable expectation of privacy and victimological impacts. However, normative ambiguity continues to create disparities in rulings and disproportionate evidentiary burdens on victims. The research recommends legislative reform through amendment of the UU ITE or enactment of specific legislation on image-based sexual abuse to provide stronger legal certainty and substantive victim protection.

Artificial Intelligence (AI) has increasingly shaped the digital transformation of higher education, particularly through its integration with Learning Management Systems (LMS). Features such as intelligent tutoring, predictive analytics, plagiarism detection, and automated grading are reshaping teaching and learning. However, questions remain regarding the readiness of higher education institutions and the acceptance among lecturers and students. This paper presents a Systematic Literature Review (SLR) of studies published between 2020 and 2025, focusing on readiness and acceptance of AI in LMS. Guided by the PRISMA framework, 220 records were identified, 85 screened, 40 assessed for eligibility, and 20 included in the final analysis. Findings highlight that readiness is largely influenced by infrastructure, digital literacy, and institutional policy, while acceptance is shaped by perceived usefulness, ease of use, trust, and behavioural intention. Although challenges such as ethics, cost, and privacy concerns persist, opportunities exist in the form of personalized learning and intelligent decision-making. The review concludes that while AI adoption in LMS is progressing globally, developing contexts such as Malaysian polytechnics require further research and targeted interventions to enhance both readiness and acceptance.

The 5-star hotel is full of beauty, futuristic design, and perfect service. One of the components that guests complain about at the Tentrem Hotel Yogyakarta is housekeeping negligence. The research method is qualitative, with data collection techniques including interviews, observations, and documentation. The results of the study show that the forms of negligence that occur in housekeeping services at Hotel Tentrem Yogyakarta are 3 (three) actions: first, negligence in cleaning guest rooms, errors in placing guests' personal belongings, and delays in providing additional requests (amenity delay). Housekeeping negligence affects guest satisfaction at Hotel Tentrem Yogyakarta by reducing the reliability and tangibles dimensions of service quality. Guests feel the hotel cannot be trusted to provide a comfortable stay experience, leading to a decrease in the empathy and assurance dimensions. Guests feel their privacy is violated, which may even lead to suspicion toward hotel staff. Efforts to improve the negligence occurring in housekeeping services at Hotel Tentrem Yogyakarta involve three actions: implementing an inspection checklist and supervisor verification before guests check-in, ensuring staff are well-trained, educated, and professional in their work, and adopting a digital logistics system to record guest requests and prioritize deliveries.

This study aims to examine: 1) the effect of perceived usefulness, perceived ease of use, and perceived security and privacy on attitude toward using; 2) the effect of perceived usefulness, perceived ease of use, and perceived security and privacy on the intention to use digital wallets in Aceh Province; and 3) the mediating effect of attitude toward using in the relationship between perceived usefulness, perceived ease of use, and perceived security and privacy on the intention to use digital wallets in Aceh Province. The data collection method employed non-probability sampling with a total of 275 respondents. Data analysis was conducted using Partial Least Squares (PLS)-based Structural Equation Modeling (SEM) via SmartPLS 4.0. The findings show that perceived usefulness, perceived ease of use, and perceived security and privacy positively influence attitude toward using, which subsequently affects the behavioral intention to use. These results indicate that individuals in Aceh are more likely to adopt digital wallets when they perceive them as beneficial, user-friendly, and secure. Furthermore, the mediating role of attitude emphasizes its importance in strengthening the relationship between user perception and the intention to use digital wallet technology (t-value = 5.717, p-value = 0.000).

In today’s digital era, the internet and social media have become an essential part of teenagers’ daily lives. Almost every day, they communicate, search for information, and share stories through various digital platforms. However, many are still unaware of how important it is to protect personal data and understand ethics when using social media. This lack of awareness often leads to problems, ranging from account misuse, the spread of hoaxes, to cases of online bullying that can harm many people.To address this issue, a training program was specifically designed for junior high school students to equip them with safe and responsible digital skills. The training not only provided theoretical explanations but also included real case simulations and hands-on practice so students could easily understand and apply the lessons. The materials covered simple ways to protect accounts, recognize signs of hoax news, and build healthy and positive interactions in the digital space.The results of the training showed that students became more aware of the importance of protecting privacy, more cautious before sharing information, and more respectful of ethics in every digital interaction. With a fun and practical approach, this program has proven effective in improving students’ digital literacy and fostering wise attitudes in using social media. In the future, such training is expected to be continuously implemented in schools as an effort to build a safer, healthier, and more cultured digital ecosystem

The process of managing, creating, or organizing something in the best way to achieve the best or ideal results is called optimization. Optimization aims to maximize or minimize certain values ​​to produce effective, successful results consistent with desired goals. You can communicate and interact with people you've never met in person using social media sites like Facebook. Online friendships can even be formed. Social media platforms like Facebook. Social media should be used with caution because almost everyone uses it. Facebook can be used for entertainment, education, promotion, and information sharing, all of which can be beneficial if done correctly. Everyone who uses Facebook should be aware of communication ethics, maintain their privacy, and refrain from sharing offensive content to maintain the security and usability of the platform. The implementation involves socialization methods and question-and-answer sessions with mothers at a social gathering. April 15, 2025. This activity took place at a resident's home. In addition to providing optimization training, the activity also aimed to improve communication between the village head and residents through the active involvement of participants. The goal was also to create a positive discussion atmosphere to improve community well-being and foster a stronger sense of togetherness and trust for future village growth. This will allow for identification of existing communication barriers and collaborative work to find solutions.

This study analyzes the impact of implementing Indonesia’s Law No. 27 of 2022 on Personal Data Protection (PDP Law) on cybersecurity in the e-business sector. Using a normative qualitative approach through literature analysis, this research examines the regulation’s implications for technical infrastructure, compliance procedures, and human resource capacity development within e-business operations. The findings indicate that although the PDP Law provides a comprehensive legal framework and human-centered principles for personal data protection, its implementation faces technical, operational, and economic challenges, particularly for micro, small, and medium enterprises (MSMEs). These challenges include limited security infrastructure, lack of technical expertise, and high investment costs. Nevertheless, adopting strategies such as multi-layer security architecture, zero-trust security model, privacy by design, and strengthening human resource capacity can enhance consumer trust, industry credibility, and the global competitiveness of Indonesia’s e-business sector. This study contributes to the literature by bridging the gap between personal data protection regulation and cybersecurity practices while offering strategic recommendations for both business actors and regulators.

Artificial Intelligence (AI) has significantly transformed the design industry by introducing innovative tools that enhance efficiency, creativity, and personalization in the design process. This article explores the impact of AI technologies on the practice of modern designers, from the early stages of idea generation to the final execution of projects. By analyzing case studies, conducting surveys, and reviewing recent literature, the study reveals that AI functions not only as a tool but also as a collaborator that expands the boundaries of human creativity. It allows designers to explore new possibilities and push the limits of traditional design processes. However, the integration of AI into design practices also raises important ethical and professional challenges, such as concerns about job displacement, data privacy, and the potential loss of human touch in the creative process. Despite these concerns, the findings highlight that embracing AI is crucial for designers to remain competitive and sustain their careers in the rapidly evolving digital era. Adapting to AI technologies, understanding their capabilities, and effectively incorporating them into creative workflows will enable designers to stay relevant and thrive in a landscape where technology continues to reshape the industry. This study provides insights into the evolving relationship between human designers and AI, offering recommendations for future research and practice in the field of design.

The widespread use of digital images, driven by low-cost, handheld acquisition devices, has increased the need for robust security measures to safeguard privacy. This demand is further underscored by rising identity theft and other image-related crimes. This study presents a chaos-based experimental evaluation of contemporary image encryption algorithms. Owing to intrinsic properties such as sensitivity to initial conditions and pseudo-randomness, chaos theory has become increasingly prominent in image encryption. Five chaos-based image encryption schemes were selected and applied to a dataset of 26 color images. The evaluation covers both encryption performance and cryptographic security. Decryption quality is measured using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and DeepEns. Cryptographic security is assessed using entropy, correlation coefficient, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), average and maximum deviation, and histogram analysis. Experimental results indicate that all evaluated schemes demonstrate strong cryptographic security and comparable encryption performance, with broadly similar effectiveness across methods.

This systematic literature review examines the philosophy of science approaches to user security in distributed devices, such as IoT and Federated Learning. The review was conducted in response to the exponential growth of connected devices and the increasing security threats, including cyberattacks, data breaches, and unauthorized access. As distributed systems become more complex, traditional security approaches, such as cryptography and differential privacy, are often insufficient to address the ethical, philosophical, and contextual challenges that arise in these ecosystems. Distributed devices, especially in IoT and Federated Learning contexts, rely on vast amounts of personal data. This data, often stored or processed in decentralized environments, creates significant risks to user privacy and system integrity. As the number of connected devices grows, security risks multiply, creating challenges in maintaining user trust, privacy, and overall system resilience. Conventional techniques, such as encryption, only focus on technical aspects, often neglecting the deeper philosophical dimensions, such as the nature of knowledge, privacy, and fairness in these systems. These gaps highlight the need for a more nuanced approach that incorporates philosophical perspectives into security frameworks. This study uses a systematic literature review method based on the PICOC (Population, Intervention, Comparison, Outcome, Context) framework to analyze the relevance of epistemology, ontology, and ethics in strengthening system security. By examining the foundational principles of how knowledge is constructed (epistemology), what entities exist in the system (ontology), and the ethical considerations around data and user privacy (ethics), the review provides a comprehensive understanding of how philosophical concepts can be integrated into the design and implementation of security systems in distributed environments. The results reveal that epistemological principles, such as the verification and validation of data sources and models, can significantly improve the reliability and trustworthiness of distributed systems.  

The increasing number of mental health disorders in various countries has created an urgent need for innovation in the diagnosis and treatment process. This problem not only impacts individuals' quality of life but also creates a significant social and economic burden. One solution that is beginning to be widely researched is the use of artificial intelligence (AI) in the field of mental health. This research used a literature review of various previous studies discussing the role, application, and impact of AI. The results of the review indicate that AI technology, particularly in the form of digital applications such as chatbots, has great potential to support the recovery process for patients with mental disorders. AI-based chatbots can provide responsive, two-way interactions, so users feel heard and receive initial emotional support. One technical approach used is Natural Language Processing (NLP), which enables the system to understand natural human language. Simultaneously, Long Short-Term Memory (LSTM) algorithms are used to analyze language patterns and detect symptoms of depression more accurately. Various studies have reported that the application of NLP and LSTM can improve the reliability of diagnoses and provide responses tailored to user needs. Furthermore, AI can provide personalized recommendations, tailor interventions to the user's condition, and monitor mental health developments in real time. This has the potential to assist mental health practitioners in making faster and more informed decisions. However, the adoption of AI among practitioners remains relatively low. Influencing factors include limited technological understanding, limited infrastructure, and debates over ethical aspects and data privacy. Therefore, while AI has significant potential to improve the quality of mental health services, regulations, ethical guidelines, and synergy between technology and healthcare professionals are needed to ensure safe and effective implementation.

This study aims to deeply examine the role and impact of AI implementation in the B2B sales process, including implementation challenges. The method used is a qualitative approach with descriptive studies, through a literature review of scientific journals, industry reports, and relevant previous studies. The analysis results show that the application of AI in B2B sales not only improves the accuracy of marketing strategies and lead conversion, but also strengthens the concept of value co-creation through collaboration between salespeople and AI systems. Technologies such as machine learning, predictive analytics, and NLP-based chatbots have been proven to accelerate sales cycles, expand service reach, and increase productivity by up to 30%. However, implementation challenges remain, including limited digital infrastructure, a lack of competent human resources, and organizational resistance to technological transformation. Therefore, optimal AI integration requires institutional readiness, adaptive strategies, and continuous investment in technology and human resource development. These findings provide theoretical and practical contributions to the development of AI-based B2B sales strategies, particularly in the context of the digital industry in Indonesia. Furthermore, the application of AI in B2B sales also opens up new opportunities for service personalization. With the support of real-time data analysis, companies can better understand the specific preferences and needs of their business partners. This enables the development of more targeted communication strategies and the enhancement of long-term relationships with business customers. AI also plays a role in reducing human error through automated systems that can validate data, provide predictive recommendations, and support faster and more accurate strategic decision-making. Furthermore, the adoption of AI in B2B requires clear regulations and governance, particularly regarding ethical data use and information security. Companies must be able to balance the use of technology to increase efficiency with the protection of privacy and consumer rights.

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 digital technology has brought about significant changes in the way humans communicate and live their daily lives. One important innovation is Artificial Intelligence (AI), one tangible manifestation of which is the chatbot as a virtual friend. This study aims to examine the role of chatbots as virtual friends through a literature review approach. The results of the study indicate that chatbots can serve as a potential, easily accessible tool for providing emotional support. Chatbots are able to create a safe space for users, especially Generation Z, to express themselves and overcome loneliness. However, the relationship between humans and chatbots is complex. Chatbots can mimic supportive responses, but as algorithmic systems, their ability to experience true empathy is very limited. Users' awareness that responses are coming from a machine also influences perceptions of trustworthiness and the quality of the interaction. On the other hand, the use of chatbots also raises serious ethical challenges, such as data privacy issues, the potential for over-dependence, and increased loneliness if chatbots are used as a substitute for real social interaction. Therefore, the development and use of chatbots as virtual friends must be carried out with a critical understanding and ethical approach. Technology design oriented towards humanitarian values is needed so that the presence of chatbots does not diminish the essence of human relationships but instead becomes a psychosocially beneficial complement.

The rise of online loans (commonly known as pinjol) reflects the broader transformation of conventional financial systems into digital platforms, influenced heavily by the rapid development of financial technology (fintech). While online loans offer ease and accessibility, their implementation has raised significant legal concerns—particularly relating to the violation of privacy and the rights of third parties who are not directly involved in the loan agreement. One of the main legal issues occurs during the debt collection process, where third parties—often relatives, colleagues, or acquaintances of debtors—are subjected to intimidation, unlawful dissemination of personal data, and public defamation. These practices are not only unethical but also infringe on the privacy and dignity of uninvolved individuals. This article employs a legal research method using a normative approach. As a normative legal study, it analyzes laws, regulations, and legal literature relevant to the problem. The study finds that current legal regulations do not adequately protect third parties from the harmful practices associated with online loan collections. In response, there is a pressing need for regulatory reform. This includes strengthening personal data protection laws, enhancing supervision mechanisms over fintech companies, and ensuring that legal standards are consistently enforced. Reformulating these regulations will help address the legal vacuum and ensure greater legal certainty and protection for all individuals affected by online loan transactions. Through comprehensive policy changes and stronger enforcement, the negative impact of online loans can be mitigated, safeguarding both borrowers and uninvolved third parties.

The development of digital technology has had a significant impact on people's lives, including the protection of citizens' privacy rights. One key issue that has emerged is the management and protection of personal data, which is increasingly vulnerable to misuse. This study aims to examine and compare the personal data protection provisions stipulated in the 2024 Electronic Information and Transactions Law (ITE Law) and Law Number 27 of 2022 concerning Personal Data Protection (PDP Law). The research method used is a normative approach with comparative study techniques. The study focuses on the legal substance, scope of data protection, and institutional roles in implementing both regulations. The analysis shows that the ITE Law remains general in nature, lacking specific detailed regulations governing personal data protection mechanisms. Meanwhile, the PDP Law presents a more systematic and comprehensive specific regulation, referencing international principles such as the General Data Protection Regulation (GDPR) in the European Union. However, several implementation challenges exist, including overlapping authority between institutions, inconsistencies in legal norms, and limited adequate legal infrastructure. This situation has the potential to create regulatory dualism and complicate the law enforcement process. Therefore, steps are needed to harmonize the ITE Law and the PDP Law, strengthen the capacity of institutions responsible for data protection, and increase the digital literacy of the public so that citizens' digital rights can be optimally protected in the digital era.

Improvement amount Distributed Denial of Service (DDoS) attacks in cloud infrastructure and edge computing demands solution adaptive, distributed, and efficient detection in a way computing. Research This propose an optimized Federated Learning (FL) based DDoS detection model using Centroid Opposition-Based Bacterial Colony Optimization (COBCO) to training the Elman Neural Network (ENN). The proposed architecture consists of of two components Main: on the edge node side, a hybrid Convolutional Neural Network–Gated Recurrent Unit (CNN–GRU) model is used to extraction feature local from traffic data network, while on the server side, model parameters from each node are collected and used for training an optimized ENN with COBCO. Approach This aim increase accuracy detection at a time maintain efficiency local data communication and privacy. In progress experimental, model tested use three benchmark datasets: NSL-KDD, CICIDS2017, and CICDDoS2019. The preprocessing process includes feature encoding categorical, normalization numeric, class balancing using SMOTE, as well as validation cross (k-fold). Initial results show that combination of FL, CNN–GRU, and COBCO–ENN produces improvement significant in accuracy and time convergence compared to approach conventional such as PSO, GA, and non- federative models. In addition, the proposed model capable maintain performance detection tall although executed in edge environment with limitations source Power.  Study This give contribution important in development system scalable, privacy-preserving, and adaptive intelligent DDoS detection to dynamics Then cross modern network. Integration of FL and COBCO in ENN training shows potential big for used in implementation real in cloud-edge infrastructure. In addition, the proposed model demonstrates strong scalability and adaptability, making it highly suitable for dynamic and evolving network environments.

This study employs a normative juridical approach to examine the legal aspects of implementing financial technology (fintech) in healthcare financing in Indonesia. The rapid development of fintech offers potential solutions for addressing financial barriers in healthcare access. However, it also presents legal and regulatory challenges, particularly concerning consumer protection, data privacy, and institutional coordination. The analysis focuses on several key legal instruments, including Law No. 8 of 1999 on Consumer Protection, Law No. 11 of 2008 on Electronic Information and Transactions (ITE), Law No. 17 of 2023 on Health and its implementing regulation, Government Regulation No. 28 of 2024, and Law No. 27 of 2022 on Personal Data Protection. Additionally, regulations issued by the Financial Services Authority (OJK), which govern the operations of fintech companies in Indonesia, are also considered. The findings indicate that while there is a growing regulatory framework supporting fintech integration into the health sector, several gaps remain, particularly in terms of coordination between regulatory bodies and stakeholders in health and finance. The study identifies the need for comprehensive policy harmonization to ensure that fintech-based healthcare financing systems are secure, transparent, and inclusive. Furthermore, it emphasizes the importance of strengthening data protection mechanisms and enhancing regulatory oversight, especially for fintech services operating in partnership with healthcare providers. As fintech continues to reshape the landscape of healthcare financing, robust legal safeguards must be developed to mitigate potential risks and ensure equitable access to health services. The study concludes by recommending an integrated legal and institutional approach to support the safe and ethical implementation of fintech in Indonesia's healthcare sector.

WhatsApp is one of the most widely used messaging platforms, offering fast and simple communication. Among its active users are students from Islamic boarding schools (santri), including those involved in micro, small, and medium enterprises (MSMEs). However, despite its convenience, many users lack awareness regarding digital safety and privacy, exposing them to cyber risks such as phishing, scams, and identity theft. In Nusukan, Surakarta, this issue is particularly relevant for santri who rely on WhatsApp for both academic and business communication. This community service initiative was conducted at Al-Mukminun Islamic Boarding School in Nusukan, Surakarta, with the aim of increasing awareness and understanding of safe WhatsApp usage among MSME santri. The program consisted of counseling sessions, which included lectures and interactive discussions tailored to the participants’ needs. Key topics included how to adjust privacy settings, identify suspicious links and messages, protect personal data, and recognize common cyber threats. Participants responded positively to the training. Feedback showed that 80% of them reported they would avoid clicking unknown links in messages. Another 80% stated they would refrain from sharing personal information with strangers. Furthermore, 80% expressed their commitment to regularly updating the WhatsApp application to ensure optimal security features are in place. This program successfully raised awareness and empowered santri with essential knowledge about digital communication safety. It highlights the importance of integrating communication psychology and practical digital literacy into community education to support secure online behavior for young entrepreneurs. Overall, this training shows that a contextual and applicable communication psychology approach is very effective in forming positive digital awareness and behavior in religious-based communities such as MSME students.

The rapid expansion of Indonesia’s digital economy and the enactment of the Personal Data Protection Law (Law 27/2022) have exposed significant shortcomings in the resolution of data-related disputes under existing judicial and administrative frameworks. Public adjudication of sensitive data conflicts can erode trust, impose reputational damage, and delay reparative outcomes, while courts often lack specialized expertise in technology and privacy. Drawing upon international precedents including the European Data Protection Board’s Article 65 GDPR mechanism, the EU–US Data Privacy Framework arbitration annex, and the European Patent Office’s data-protection arbitration rules this study examines the urgency and feasibility of establishing a dedicated Data Dispute Arbitration Forum in Indonesia. Through comparative analysis, it identifies core design elements such as expert-appointed tribunals, streamlined online procedures, confidentiality safeguards, clear enforcement under the New York Con-vention, and mechanisms for restorative remedies beyond fines. Anchored in Pancasila’s social-justice ethos and Indonesia’s ADR law (Law 30/1999) and ITE Law, the proposed institutional architecture integrates online dispute resolution (ODR) protocols, data-minimization and cybersecurity guidelines, and publicly anonymized award publication to foster legal certainty and raise awareness of data-protection obligations. A stakeholder impact assessment demonstrates that such a forum would benefit individual data subjects through low-cost, expeditious relief; controllers and processors through predictability and trade-secret protection; regulators through expert findings; and foreign investors through alignment with global data-governance standards. By aligning domestic legal values with international best practices, the specialized forum promises to bolster enforcement, restore public trust, and strengthen Indonesia’s competitiveness in the global digital marketplace.