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This study analyzes the influence of ease of use and security on customer satisfaction with the mobile banking services of Bank Sumsel Babel Syariah, particularly among students of the Faculty of Islamic Economics and Business at UIN Raden Fatah Palembang. Using a quantitative approach, data were collected through questionnaires from 100 respondents. The results indicate that ease of use does not have a significant effect, while security has a positive and significant impact. Collectively, ease of use, security, and trust contribute 78.5% to customer satisfaction variability. The study recommends enhancing security systems and usability of the mobile banking application, as well as educating customers on safe usage practices.

Job Involvement is a situation in which an individual feels a psychological attachment to their work and holds a strong belief in completing their tasks to achieve a high level of self-esteem. Safety performance refers to the worker's performance in prioritizing safety in the workplace by adhering to the applicable health and safety regulations. The purpose of this study is to determine the effect of Job Involvement on Safety Performance among ship crew members in improving the safety and security system of maritime operations. The research was conducted at PT. Tonasa Lines, Biring Kassi, Pangkep Regency, South Sulawesi Province. The sample in this study consisted of 100 participants. The sampling techniques used in this research were both probability sampling and non-probability sampling. The method used in this research was quantitative, using the Job Involvement and Safety Performance scales. The data analysis was performed using the Product Moment correlation technique with the assistance of the SPSS 28.0 for Windows program. The results showed a significant positive relationship between the Job Involvement variable and Safety Performance in improving the maritime safety and security system. The significance level was below or equal to 0.040 (p ˃ 0.01), so Ha is accepted and Ho is rejected with a 5% margin of error probability.

The digitalization of the banking sector, driven by the Fourth Industrial Revolution, has significantly impacted the ease of financial transactions through digital banking services. However, this progress also creates vulnerabilities to cybercrimes, particularly phishing, which aims to steal customers' personal data via fake websites or messages. This article examines relevant legal frameworks, including Law No. 19 of 2016 on Electronic Information and Transactions (EIT Law), the Indonesian Criminal Code (KUHP), and regulations issued by the Financial Services Authority (OJK), such as POJK No. 12/POJK.03/2018 on Digital Banking Services. Employing a normative qualitative approach, the study explores the legal protection available to customers as phishing victims and the responsibilities of banks in preventing and addressing such threats. This article recommends strengthening banks' technological security systems, enhancing customers' digital literacy, and enforcing laws more effectively to establish secure and reliable digital banking services.  

Security of electronic medical records (EMR) data is very important in maintaining the confidentiality, integrity, and availability of sensitive patient information. This study aims to conduct a security analysis of the EMR application used at UPTD RSD Besemah Pagar Alam City using the Penetration Testing method. This method is carried out to identify, exploit, and provide solutions to potential vulnerabilities in the EMR application system. Penetration Testing is carried out through several stages, namely information collection, scanning, exploitation, and post-exploitation, using tools such as Nmap, and OWASP ZAP. The results of the study showed several vulnerabilities in the application, including SQL Injection, Cross-Site Scripting (XSS), and weaknesses in authentication management that could allow unauthorized access to patient data. In addition, exposure to sensitive data that was not properly protected was also found. Based on the results of this test, several recommendations were made to improve system security, such as updating security patches, implementing encryption on all sensitive data. By implementing the recommended mitigation steps, the security of the EMR system at UPTD RSD Besemah is expected to be significantly improved, so that the risk of data leakage can be minimized. This research provides a real contribution in strengthening the security of electronic medical record applications. and is expected to be a reference in improving security systems in other health care institutions.    

This study aims to analyze the Level of Service (LoS) at the international departure terminal facilities at I Gusti Ngurah Rai Airport, Bali, in accommodating the growth of passenger traffic. Referring to IATA standards, PM 178 of 2015, and PM 41 of 2023, this research evaluates the performance of facilities such as passenger and baggage screening, check-in, immigration, and waiting areas. The research method used is qualitative, with data collected through observation, interviews, and documentation. The results show that the international departure terminal facilities meet the established service standards and are capable of handling passenger congestion during holiday seasons (high season and peak season). Efforts made by airport management include terminal expansion, queue management, and the enhancement of security systems with the latest technology. In conclusion, the Level of Service at I Gusti Ngurah Rai Airport is categorized as good and complies with existing standards, but infrastructure development is still needed to accommodate future increases in passenger numbers.

Security systems in the maritime sector are crucial for preventing criminal activities and theft on board ships. The physical key systems commonly used today have vulnerabilities that can be exploited by unauthorized individuals. This research aims to design and test a smart door lock system using facial recognition with the ESP32 Wrover cam and a 4x4 Keypad as an additional security measure. The test results show that the system successfully recognizes faces with a 90% success rate at a distance of 15-100 cm, although there is a decrease in efficiency when more than one face is registered. The system also demonstrated 100% success in

This study aims to investigate the identification, assessment, and control of operational risks in the travel industry, with a focus on PT Yuk Kita Tour. Direct observation and interview methods are used to identify the risks faced by the company. Risk assessment is conducted by considering the likelihood of occurrence and its impact on the company's operations, followed by appropriate mitigation strategies. The analysis results show that risks such as online booking system disruptions, lack of staff training, currency exchange rate fluctuations, regulatory changes, natural disasters, disease outbreaks, transportation delays, and terrorism threats affect operational efficiency and customer satisfaction.To control these risks, PT Yuk Kita Tour implements a comprehensive mitigation strategy, including improved cybersecurity systems, staff training programs, currency hedging strategies, active regulatory monitoring, travel insurance, strict health policies, cooperation with transportation operators, and clear security information to customers. The implementation of these risk control strategies has had a positive impact on the company's performance, with year-on-year increases in revenue and customer satisfaction. This study provides insights into the importance of operational risk management in the travel industry and demonstrates that a proactive approach to risk identification, assessment, and control is possible. This study provides insight into the importance of operational risk management in the travel industry and demonstrates that a proactive approach to risk identification, assessment, and control can improve operational efficiency and customer satisfaction. The practical implication of this study is the importance of continuously monitoring existing risks, adapting control strategies, and involving stakeholders in risk management to ensure sustainable business continuity and superior customer service in a dynamic business environment.

Behind the widespread proliferation of malware, IT experts have developed robust security systems to minimize the risk of malware infection. In the Windows security system, numerous software solutions have been created to prevent malware threats, including Windows Defender, which serves as the core of Windows security, virus & threat protection, real-time protection, firewall & network protection, account protection, and many more. This study uses a qualitative approach based on literature review. The results indicate that by integrating machine learning technology, enhancing security features, and adopting a layered approach, the strategy for developing the Windows operating system has successfully strengthened protection against malware threats. These measures not only improve the ability to detect and respond to threats but also ensure that users can enjoy a safe and protected computing experience.  

The presence of artificial intelligence (AI) technology has revolutionized efforts to protect data in offices. The challenges organizations face in maintaining information security are becoming increasingly complex as technology advances, but the benefits of AI provide an effective solution to optimize information security. In this summary, we discuss the challenges and benefits of AI in office data protection, focusing on enhancing information security.The first challenge is the increasing complexity of cyber attacks. Attackers are constantly looking for new vulnerabilities and using more sophisticated attack techniques to breach security systems. Adequate data protection is needed to address this challenge and prevent unauthorized access to critical company information. Additionally, a lack of knowledge about managing and monitoring security systems is a major challenge for many businesses.However, the use of AI to protect office data offers several advantages. First, AI's ability to quickly and accurately detect security threats aids in early detection of cyber attacks. Predictive analysis supported by AI can also detect dangerous patterns and prevent attacks before they occur. Furthermore, using AI to automate security processes can optimize operational efficiency and accountability for events that occur. AI-based security can significantly reduce the risk of data breaches and cyber attacks.The use of AI technology in office data protection is not only a supportive tool but also an innovative and efficient solution to address increasingly complex challenges in information security. We hope this overview provides a deeper understanding of the challenges and benefits of AI in protecting office data, as well as efforts to optimize information security in this digital era.  

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.

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