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The digital era has significantly transformed the face of education. The integration of technology in learning through digital devices, online platforms, and multimedia resources has created a dynamic learning environment and enriched the learning experience for students. However, its implementation faces challenges such as technology access gaps, lack of technology skills among educators, data privacy issues, curriculum alignment, and negative internet content. Collaboration among stakeholders is needed to address these challenges. Technology-based education offers opportunities for improving accessibility, flexibility, personalized learning, and innovative teaching methods. Interpreting the results of technology use in education is important to optimize its benefits and formulate effective implementation strategies according to diverse educational contexts.  

This study examines the impact of artificial intelligence (AI) on the dynamics and ethics of the workplace environment at PT COLAB PROSPERITY JAYA, a company engaged in the coconut product export industry. Using a qualitative approach, this research involved in-depth interviews with employees at various levels to explore how AI affects work efficiency, decision-making, ethical issues, and employee interactions. The results indicate that AI improves efficiency and supports decision-making with accurate data. However, there are serious ethical concerns, especially regarding data privacy and algorithmic bias. Furthermore, although AI facilitates task management, it also has the potential to reduce social interactions that are crucial for creativity and teamwork. This study suggests the need for stronger policies and ethical training to ensure that AI is integrated in a responsible and fair manner, emphasizing the importance of balancing the benefits of technology with human values in the development and application of AI in the workplace.

Protection of personal data is an embodiment of a guarantee of human rights, privacy and inviolability. The state has a full obligation to respect each other and respect the rights of every human being, as regulated in statutory regulations. Regulations regarding the protection of personal data owned by every human being, there is confusion and overlap due to the many regulations that have been established. The government, together with related officials, has formulated a draft law regarding the protection and supervision of the personal rights of every human being. This protection and supervision aims to cover the exception of personal data on the basis of a legitimate public interest, including law enforcement purposes. Arrangements that are carried out in a balance between the interests of law enforcement of a crime and the protection and supervision of the personal data of every human being, are expected to avoid actions that are carried out arbitrarily.

This research aims to investigate the role of information technology in enhancing school correspondence at MAS PAB 1 Sampali. The introduction of the research explains the importance of using information technology to improve communication effectiveness in the educational environment. The research method used is qualitative with a literature review approach, involving analysis of various related literature. The research objectives are to understand the implementation of digital platforms in school correspondence, the impact of information technology on interaction and social relations in schools, and enhancing communication effectiveness among schools. The research findings indicate that digital platforms have had a positive impact in facilitating online learning, expanding communication networks among students, teachers, and parents, and increasing engagement in school life. However, the use of technology also brings challenges related to privacy and data security that must be addressed with appropriate policies and security measures. In conclusion, information technology has great potential to enhance school communication effectiveness, but its use must be managed wisely to ensure data security and privacy are maintained.

This research explores the theoretical and philosophical underpinnings of the communication process, with a particular focus on the ethical implications and strengths in contemporary communication practice. In the context of the evolution of philosophical thought, this study combines various classical and modern communication theories. Through a qualitative approach, this study collected data from various literature studies such as books, communication journals and discourse analysis from key texts. The findings suggest that communication is not only a means of delivering messages but also as a mechanism of identity and power formation. In addition, the study revealed that communication ethics, especially in digital media, require special attention to address the challenges of honesty, transparency, and privacy. The study contributes to a deeper understanding of how philosophical principles can be applied to improve communication practices in the digital age. Thus, this study emphasizes the importance of philosophical reflection in the face of the complexity of modern communication and its impact on society

In helping MSMEs, businesses, entrepreneurship, and others to enter the digital economy and be able to compete with foreign countries, namely by implementing e-commerce or electronic commerce. The presence of e-commerce plays an important role in this 5.0 revolution era and the State's ability to manage e-commerce can have an impact on the nation's competitiveness. However, we still find that many businesses, MSMEs and so on are still reluctant to use e-commerce with the opinion that e-commerce is a fraudulent business and there are still many people who don't know the role and benefits of e-commerce. The type of research in this article is descriptive qualitative research with a literature review methodology. This writing explains that there are benefits and challenges to e-commerce itself. The benefit of e-commerce is that there are several online applications, making it easier for consumers to shop, so consumers don't need to come to the destination area where the shop is located. One of the challenges is how to maintain customer privacy, security and trust

In an era of rapid digital transformation, Indonesia faces major challenges in ensuring security, privacy and compliance are maintained. With increasing cyber threats in the country, BSSN and the Government must be more careful about potential large-scale security breaches and must prioritize building strong defense mechanisms to protect Indonesia's digital assets. Therefore, Cyber Security is the main pillar for the progress and sustainability of Indonesia's digital transformation. Then, legal provisions were issued in the form of Criminal Code Legislation and ITE Law no. 11 of 2008. The research method used in writing this article uses a qualitative method with a literature study approach. This research aims to provide an explanation regarding the compilation of national values originating from the 1945 Indonesian Constitution (UUD 1945) and the Unitary State of the Republic of Indonesia (NKRI) regarding security management. Specifically, this research examines the role of security management in dealing with cybercrime and strengthening digital defenses. It is hoped that the results of this research can be used as a reference for further research in increasing readers' insight and knowledge regarding the theme of this article.

Cyber Security for Higher Education Academic Information System (AIS) data is an increasingly important issue along with the increasing dependence of higher education on information technology. Students have their education data in the Academic Information System (AIS) which is owned by each campus. Campuses are obliged to give their students the right to privacy and the right to information. The right to privacy and limitations on the right to information include state protection of personal data. In this way, students have the right to receive protection for their personal data in the academic information system (AIS). This is regulated by the 1945 Constitution (UUD 1945) and the Personal Data Protection Law (UU PDP), which are an important foundation for regulations on data management and cyber security systems. This research uses a journal literature review method which aims to investigate the security threats faced by Academic Information System (AIS) data and to design effective protection strategies. The methods used include risk analysis, identification of system vulnerabilities, and development of appropriate security policies. The findings show that sensitive data such as student personal information and academic records are the main targets for attackers. Therefore, the need to implement security measures such as data encryption, use of double authentication, strict system monitoring, as well as training for information system users is very important. Through a policy analysis approach and literature study, this research aims to identify strategies and best practices in integrating national values into cyber security policies and practices. It is hoped that this research will provide an overview of the importance of national principles in terms of cyber security in higher education. It will also provide recommendations for institutions to improve academic information systems in accordance with the country's constitution.

The rapid development of information and communication technology has created a complex virtual environment known as cyberspace.  In this digital era, cyberspace has become the main arena for various activities, from communication, business, to social interaction.  However, this growth also poses serious challenges in managing these virtual spaces effectively.  The role of law is very important in responding to this challenge.  This study aims to explore the role of law in regulating cyberspace, as well as the associated challenges and opportunities.  The role of law in this context includes establishing regulations, law enforcement, and protecting individual rights in the digital environment.  The main challenges faced include the complex transnational nature of cybercrime, conflicting regulations between countries, as well as rapid legal adaptation to new technological developments.  However, there are also emerging opportunities in regulating cyberspace.  For example, the ability to apply a collaborative approach between states, the private sector and civil society in developing regulations that suit the unique characteristics of the digital environment.  Additionally, technology can also be used as a tool to improve law enforcement and empower individuals to protect their privacy and security online. This study uses a descriptive analysis approach to evaluate relevant literature and case studies in order to understand the dynamics of the role of law in regulating cyberspace. By understanding these challenges and opportunities, we can develop a more holistic and adaptive framework for governing cyberspace, thereby ensuring the sustainability and security of the digital environment in this digital era.

The rapid advancement of deep learning technologies has significantly transformed healthcare analytics, particularly in medical data prediction and classification. This study proposes a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) framework for multi-modal healthcare data analysis, integrating medical imaging, structured electronic health records (EHRs), and IoT-generated time-series physiological signals. The proposed architecture combines spatial feature extraction through CNN with temporal dependency modeling via LSTM to enhance predictive accuracy and clinical decision support. A quantitative experimental design was employed, utilizing multi-source healthcare datasets that underwent preprocessing, normalization, and feature engineering prior to model training. The performance of the hybrid model was evaluated using Accuracy, Precision, Recall, F1-Score, AUC-ROC, and Mean Absolute Error (MAE), and compared with conventional machine learning models and standalone deep learning architectures. Experimental results demonstrate that the proposed CNN–LSTM model achieves superior performance, with improved classification accuracy and reduced prediction error, while maintaining strong generalization capability. The findings indicate that integrating spatial and temporal feature learning significantly enhances disease detection, risk stratification, and personalized treatment planning. This approach supports the development of intelligent clinical decision support systems and scalable smart healthcare environments. The proposed framework offers a reliable and efficient solution for advanced healthcare analytics in IoT-enabled systems.

The rapid evolution of smart cities, driven by the integration of technologies such as the Internet of Things (IoT) and blockchain, has brought about significant advancements in urban infrastructure and services. However, these developments also introduce new cybersecurity challenges. Introduction: Smart cities are increasingly vulnerable to cyber threats due to the extensive use of interconnected devices and systems. A key security concern is the management of digital identities, which is essential for maintaining the integrity and reliability of city services. Literature Review: Traditional centralized identity management systems face significant security issues, including a single point of failure, data breaches, and limited user control over personal information. In contrast, decentralized solutions, particularly blockchain-based systems, offer enhanced security through their distributed nature, eliminating vulnerabilities associated with centralized models. Materials and Method: This research focuses on blockchain technology’s application in smart city identity management. A decentralized framework is proposed, leveraging cryptographic techniques, consensus mechanisms, and smart contracts to ensure data security, integrity, and privacy. Results and Discussion: The implementation of blockchain for identity management significantly improves attack tolerance, data integrity, and transparency. The decentralized approach mitigates the risks associated with central authorities, ensuring that user data remains secure and verifiable. However, scalability, interoperability, and regulatory compliance challenges remain. Blockchain solutions must be optimized for large-scale smart city applications and aligned with legal standards to achieve widespread adoption. Future research should focus on overcoming these challenges to create a more secure and resilient smart city infrastructure.

The era of globalization brings changes by causing religion, which was originally a public issue, to turn into a privacy issue. The development of religion which has become a private matter makes teenagers as identity seekers tend to implement it. The purpose of this activity is to preserve Walisongo so that it is not eliminated from the historical facts of the spread of Islam. The method applied in this service is Participatory Action Research (PAR). The results of this service activity have a positive impact on teenagers because know more about the nine saints of God who spread Islam in the archipelago and increase their understanding of the character of the saints and their struggles. The impact of getting to know the teenagers in Bebekan Tengah Village, Taman District, Sidoarjo Regency increased their admiration for the walisongo struggle which resulted in an increase in pilgrimages to the walisongo graves.

Telecommunications network planning is a crucial step in building an efficient and reliable communications infrastructure. In an era where connectivity is the backbone for various human activities, both on an individual and business scale, the importance of telecommunications network planning becomes increasingly apparent. In this abstract, we explain why telecommunications network planning is so important. First, careful planning ensures efficient use of resources, from frequency spectrum to hardware. Second, good planning can anticipate demand growth, ensuring that the network can grow in line with needs without sacrificing service quality. Furthermore, careful planning also considers security, privacy and reliability factors, which are crucial in a telecommunications environment that is constantly changing and vulnerable to threats. Thus, this abstract highlights the importance of telecommunications network planning in facing the challenges and opportunities in an increasingly connected world. With proper planning, telecommunications networks can become a strong backbone for social, economic and technological development.

Science and technology continue to develop in a more sophisticated direction. One of the technological advances in the era of globalization is marked by the Dana e-wallet. The Dana e-wallet is one of the popular alternative digital payment transactions in Indonesia because of its ease of use, benefits, risks and privacy security. The impact offered in terms of user convenience, benefits, risks and privacy security makes people interested in using this e-wallet. The aim of this research is to determine the influence of user convenience, benefits and risks on interest in using the Dana e-wallet with privacy security as an intervening variable. This research uses a causality research design with a quantitative approach and a sampling technique using Non-Probability Sampling. The population in this research is the people in Semarang City. The number of samples taken was 100 respondents. The data analysis methods used are regression analysis, path analysis, and Sobel test. The data obtained in this research was then processed using the IBM SPSS Statistics 23 program.

Artificial Intelligence (AI) has been applied to many human endeavors, and epidemiology is no exception. The AI community has recently seen a renewed interest in applying AI methods and approaches to epidemiological problems. However, a number of challenges are impeding the growth of the field. This work reviews the uses and applications of AI in epidemiology from 1994 to 2023. The following themes were uncovered: epidemic outbreak tracking and surveillance, Geo-location and visualization of epidemics data, Tele-Health, vaccine resistance and hesitancy sentiment analysis, diagnosis, predicting and monitoring recovery and mortality, and decision support systems. Disease detection received the most interest during the time under review. Furthermore, the following AI approaches were found to be used in epidemiology: prediction, geographic information systems (GIS), knowledge representation, analytics, sentiment analysis, contagion analysis, warning systems, and classification. Finally, the work makes the following findings: the absence of benchmark datasets for epidemiological purposes, the need to develop ethical guidelines to regulate the development of AI for epidemiology as this is a major issue impeding it’s growth, a concerted and continuous collaboration between AI and Epidemiology experts to grow the field, the need to develop explainable and privacy retaining AI methods for more secured and human understandable AI solutions.

The rapid expansion of e-commerce has introduced new complexities in consumer rights and legal protections. This article examines the legal framework for consumer protection in digital transactions, focusing on e-commerce fraud, data privacy, and contract enforcement. Through a comparative analysis, it identifies the strengths and weaknesses of existing regulations and suggests improvements to safeguard consumer rights in the digital age. The findings aim to inform policy development for enhancing consumer confidence and security in online transactions.

Cyber Physical Systems (CPS) are vital for managing and controlling critical infrastructures, such as industrial control systems, power grids, and transportation networks. These systems integrate digital and physical components, offering numerous benefits for industrial automation. However, the increasing interconnectivity of these systems has introduced new security vulnerabilities, particularly in anomaly detection and system reliability. This research aims to address these challenges by proposing an edge based anomaly detection framework that leverages lightweight deep learning models, specifically designed to operate efficiently on resource constrained edge devices. Literature Review: Previous studies have shown the effectiveness of anomaly detection in CPS, with traditional methods struggling to keep up with the complexity and scale of modern industrial environments. Machine learning and deep learning approaches, particularly hybrid models combining rule based systems and AI, have emerged as effective solutions for real time anomaly detection. Techniques such as model compression, quantization, and pruning are essential for adapting these models to resource limited edge devices while maintaining high detection accuracy and low latency. Materials and Method: The proposed framework integrates deep learning models such as Convolutional Neural Networks (CNNs) and Long Short Term Memory (LSTM) networks, optimized for edge computing environments. The datasets used for training and testing include industrial network traffic and sensor anomaly datasets. Model optimization techniques like pruning and quantization were applied to reduce computational overhead and energy consumption on edge devices. Results and Discussion: The framework demonstrated high detection accuracy (AUC of 0.9720) with ultra low latency (0.0019 seconds training time), making it highly suitable for real time anomaly detection in CPS. Resource efficiency was achieved by optimizing the models for edge devices, reducing energy consumption while maintaining performance. The framework also significantly improved security by identifying anomalies early, preventing potential threats to critical infrastructures. Future directions include exploring federated learning to enhance privacy and data sharing across distributed devices.

Marriage involves individual rights such as opinion, privacy non-discrimination. Early marriage is the practice of marriage involving one or both partners who are still young, where both are still under the legal age or generally recognized age of adulthood. Early marriage can be influenced by various factors, namely social, pressures. Family involvement, cultural norms, and gender inequality can also play an important role in the decision to marry early. Early marriage of minors creates legal problems, which involve violations of children's rights and also gender inequality. The age for marriage must be completely mature, which is 19 years for men and 16 years for women. If both of them are still young, or you could say like young onions, their marriage will always be filled with problems. Both of them still have the same high level of egoism, are still children and still only think for a few days. In Indonesia Regulates the second amendment to Law no. 1 of 1974 confirms that the minimum age limit is 19 years, and 16 years for women. A woman is someone who has reproductive organs which are related to the ability to give birth to children. Meanwhile, a man is someone who has reproductive organs that play a role in reproduction itself. In Indonesia, the case of early marriage is still a very serious and vulnerable issue. As reported by the KEMENKO PMK, it was stated that there were around 1.2 million cases of early marriage in Indonesia. The proportion of women aged 20-24 years who were married before the age of 18 was 11.21% of the total number of children. This means that around 1 in 9 women aged 20-24 years were married as children. Meanwhile, around 1 in 100 men aged 20-24 years were married as children. Due to the large number of cases regarding underage marriage, the government's role must be agile and fast in dealing with important cases like this. The government must play a role in preventing how to prevent cases of underage marriage from increasing every year.

The development of information and communication technology facilitates transactions, including through e-commerce, but has the potential to present criminal acts of data theft and violations of user privacy. This research investigates the case of data leakage in the Tokopedia application in criminal law and corporate liability by Tokopedia. The analysis shows that Tokopedia can be criminally liable for its negligence in maintaining the security of personal data, such as the weakness of the data security system (encryption) and the lack of vigilance against hacker attacks. Tokopedia has several obligations in protecting users' personal data. This case shows the importance of corporate criminal liability and the company's obligation to protect users' personal data. Using the normative juridical method and statutory approach, primary data is obtained from the Tokopedia 2020 case study, while secondary data comes from primary and secondary legal sources. The results show that the Tokopedia data leak in 2020 is a criminal offense due to the negligence of PT Tokopedia, which is in accordance with the criminal law principle of Culpa Lata Unconscious. The Personal Data Protection Law emphasizes the responsibility of PT. Tokopedia in protecting personal data. Law enforcement needs to take firm action against the perpetrators of criminal acts to provide a deterrent effect.

The rapid spread of infectious diseases remains a major global health threat, and early detection is vital to minimize their impact. This research investigates the role of predictive modeling using big data in the early detection of infectious disease outbreaks. The primary objective of this study is to assess the effectiveness of big data systems in forecasting potential outbreaks and the implications of these forecasts for public health systems. The study employs machine learning-based predictive models to process large health datasets, including electronic health records, sensor data, and social media information. The results demonstrate that the predictive model achieved an accuracy rate of 87%, significantly surpassing traditional methods in terms of early detection. By integrating various data sources such as medical records, sensor networks, and real-time digital traces, the system is capable of providing more accurate, timely predictions, which can greatly improve the ability of public health authorities to respond effectively to emerging health threats. Furthermore, the application of big data in public health not only improves the speed of response but also enhances the allocation of resources, allowing for more targeted and efficient interventions. Despite these successes, challenges remain, particularly in relation to data quality, privacy, and regulatory issues, which could hinder the broader implementation of such systems. Thus, collaboration between government agencies, healthcare institutions, and technology developers is essential to overcome these obstacles and ensure the sustainable integration of big data into public health infrastructures. This research highlights the significant potential of big data to transform public health responses, offering valuable insights for future epidemic management strategies.