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The exchange of information in the digital era has become a general need for society. However, the information sent often has a public or confidential nature. Therefore, security is needed so that confidential information remains safe. Cryptography is a field of knowledge used to secure information using encryption and decryption processes. One of the cryptographic methods used is the permutation method, which changes the layout, sequence, or structure of data into a form that is difficult to understand without knowledge of the exact key. Implementing cryptography using the permutation method in Android-based applications can increase the security and privacy of user data, as well as protect sensitive information from unauthorized access. This research aims to implement permutation method cryptography in Android-based applications to protect the confidentiality or privacy of user data. By using the permutation method, the sequence of bits or characters in the data is scrambled so that it is difficult for unauthorized parties to understand. The research results show that the implementation of permutation method cryptography in Android applications can provide a higher level of security in maintaining data confidentiality. However, it is worth considering that simple permutation methods may not be secure enough to deal with more sophisticated attacks. Therefore, choosing a stronger cryptographic method needs to be considered to achieve a higher level of security. In conclusion, implementing cryptography using the permutation method in Android-based applications can increase the security and privacy of user data. The permutation method is able to randomize the sequence of bits or characters in the data so that it is difficult for unauthorized parties to understand. However, for a higher level of security, it is necessary to consider stronger cryptographic methods.

Power transformer theft, a pervasive issue disrupting critical infrastructure, necessitates the development of cost-effective and energy-autonomous security solutions. This paper presents the design and implementation of a detection-focused anti-theft framework that integrates a Raspberry Pi Zero W, camera module, and passive infrared (PIR) motion sensors powered by a solar system for continuous monitoring. The system is designed for remote, off-grid deployment, utilizing a headless Raspberry Pi powered by a 5V solar panel and power bank to ensure energy autonomy. Upon motion detection, captured images are processed on the edge device using OpenCV’s Haar Cascade classifier, optimized for upper-body detection to minimize false positives and verify human presence. Captured images are processed locally on the edge device using OpenCV’s Haar Cascade classifier to confirm human presence before an alert is sent to the mobile application, emphasizing real-time operation and low latency. Once an intrusion is confirmed, the images are saved locally and uploaded via the Secure File Transfer Protocol to a custom-developed Android application. The app provides a dedicated remote monitoring interface, enabling secure file transfer and system access, while providing users with immediate notifications and image management capabilities. The system emphasizes low power consumption, real-time operation, and low deployment cost. Tests over 200 triggered events under varied environmental conditions achieved 90% detection accuracy with an average latency of 4.5 s. Solar autonomy was maintained for approximately 24 h under normal operation. It is concluded that the integration of solar power, edge computing of images, and mobile monitoring provides a feasible, scalable, and financially viable framework for securing transformers, especially in resource-constrained environments.

The synchronization of mutex and semaphore mechanisms is an important technique in operating systems for managing concurrent resource access in multi-threaded environments. In the Android operating system, which relies on thread-based programming to maintain performance and responsiveness, these two mechanisms play a vital role in preventing race conditions and ensuring data integrity. A mutex is a locking object that ensures that only one thread can access a specific resource at a time, while a semaphore controls access to a limited number of resources by counting the number of threads that can access them simultaneously. In Android, these mechanisms are implemented using the Lock class for mutexes and the Semaphore class for semaphores, both of which can be used to control synchronization between threads in Android applications. This paper will discuss the application of these two mechanisms in the context of shared resource management, as well as a comparison of their performance and advantages in dealing with complex multi-threading scenarios on Android. Emphasis will also be placed on the challenges faced in using these two mechanisms in Android applications, as well as how proper programming can avoid deadlocks and improve application efficiency.

This study aims to design and develop an interactive learning medium based on Augmented Reality (AR) for the subject of Basic Electronics Engineering, particularly on the topic of active and passive electronic components, in order to enhance the understanding and learning motivation of tenth-grade students at SMK Negeri 5 Padang. The development method used is the Multimedia Development Life Cycle (MDLC), which includes the stages of conceptualization, design, material collection, production, testing, and distribution. The final product of this research is an Android application utilizing AR technology to display 3D objects of electronic components, equipped with learning materials, educational videos, interactive evaluations, and a scan marker feature. The results of the development and implementation of this learning medium show that the Android application serves as an interactive medium that supports the learning process through Augmented Reality technology. The application received a score of 93% from the Media Expert, categorized as “Valid,” and 89.3% from the Material Expert, also categorized as “Valid.” Furthermore, the practicality test conducted with students showed an overall score of 93.15%, categorized as “Very Practical.” Based on the design results and validation by the Media Expert and Material Expert, it can be concluded that this interactive learning medium based on Augmented Reality technology is highly feasible for use. Furthermore, the implementation of this application in the learning process shows an increase in student participation and enthusiasm during the learning activities. Students appear more interested in exploring the material through 3D visualizations provided by AR technology, compared to conventional methods. The interactivity offered by the application, such as evaluation features and educational videos, also helps students understand concepts in a deeper and more enjoyable way. This shows that the integration of AR technology in learning media not only improves the effectiveness of the quality of the material.

Number recognition is a critical skill in early education, laying the foundation for digital literacy and mathematical understanding. However, traditional methods of teaching number recognition often lack the interactivity and engagement necessary for effective learning, particularly for young learners. This study proposes the development of a deep learning-based Android application aimed at enhancing the number recognition process by providing an interactive and visual learning experience. The application utilizes a Convolutional Neural Network (CNN), a type of deep learning model, to recognize handwritten numbers, offering users an innovative and engaging way to learn and practice number recognition.In the proposed application, users can draw numbers on their devices, and the system will immediately provide feedback regarding the accuracy of the drawn numbers. The CNN model will be trained on a comprehensive dataset of handwritten digits to ensure high accuracy in recognition. This real-time feedback loop is designed to help users learn the correct form of numbers while also introducing the foundational concepts of deep learning. The main objective of this application is to provide an accessible, interactive platform for learning number recognition, especially for novice learners who may be unfamiliar with basic concepts in machine learning and digital literacy. By integrating deep learning technology, the application not only supports the learning of number recognition but also serves as an introduction to artificial intelligence (AI) concepts in a practical, easy-to-understand format. Furthermore, the application is designed to be user-friendly, ensuring that it is suitable for a wide range of learners, including children and beginners. The application aims to combine the fundamental principles of deep learning with a practical, hands-on learning experience, fostering a deeper understanding of both number concepts and the potential of AI in everyday life.

Electric Vehicles Require A Reliable Monitoring System To Maintain Their Efficiency And Safety. This Study Designs A Monitoring System For Battery Condition And Vehicle Location Based On The Esp32 Microcontroller And The Mit App Inventor Application. The System Uses The Pzem 017 Sensor To Monitor Voltage, Current, Power, Energy, As Well As Battery Capacity And Health, And The Neo-7m Gps Module For Location Tracking. Data Is Displayed In Real Time Through An Android Application. Test Results Show That The System Provides Accurate Information, With Minimal And Statistically Insignificant Measurement Errors According To The Paired T-Test. The System Also Remains Stable At Various Vehicle Speeds (Anova), And The Location Tracking Demonstrates An Average Accuracy Of 4.77 Meters In Open Areas. In Enclosed Areas, The Error Increases To An Average Of 10.26 Meters. The System Is Also Capable Of Automatically Calculating Battery Capacity And Health. Overall, The Developed System Proves To Be Effective, Efficient, And Flexible In Supporting The Reliability And Safety Of Electric Vehicles.

The rapid evolution of digital technology has significantly impacted various sports, including niche ones like petanque. This study explores the perceived benefits and barriers of using an Android-based application for scoring and statistics management in petanque, a sport gaining popularity in Indonesia. Traditionally, performance assessment in petanque relied on manual, paper-based methods, prone to inaccuracies and inefficiencies. An Android app, Petanque Match Statistics, was developed to address these challenges, offering real-time data accuracy, improved workflow, and enhanced performance analysis. This study employed a quantitative approach, surveying 50 participants (35 players and 15 coaches) in Surabaya, Indonesia, to assess their impressions of the app's usability, accuracy, efficiency, and overall satisfaction. Results indicated high ratings across all parameters, with no significant differences between players and coaches. The app was commended for its intuitive design, reliability, and time-saving efficiency. Findings highlight the potential of digital solutions to modernise petanque match administration, enhance strategic decision-making, and improve the user experience. The study underscores the importance of user-centred design in facilitating the adoption of digital advancements in sports, offering valuable insights for future developments in petanque and other emerging sports.

Push Up is a physical activity carried out by individuals that aims to strengthen the muscles of the body, namely the muscles of the arms, shoulders and chest. Designing an IOT-based detection and monitoring system with the aim of making it easier for tool users to know the number of repetitions and the number of calories used automatically. Detectoring with the help of four proximity sensors to detect motion when doing push-ups and monitoring using an android application made specifically for the device. The component used is NodeMCU ESP8266 as a microcontroller. The parameters displayed in the application include a column of push-up repetitions, a column for the number of calories used, and a graph of increasing push-up repetitions. The tool testing method was carried out 15 times for data collection with 20 push-up repetitions for each data collection. The results of the test, obtained an error percentage of 1.33%. So that this tool can help users to monitor the repetitions that have been done and find out the amount of calories used.

The XYZ Health Center faces challenges in managing the outpatient registration process manually, often resulting in long queues, extended waiting times, and data inaccuracies. To address these issues, this study aims to design and develop an Android-based outpatient registration application. The application is intended to simplify the registration process for patients, allowing them to register for visits without needing to visit the health center in person, while also enabling healthcare staff to manage patient data more efficiently. The methodology employed in this study includes requirements analysis and system design using the Unified Modeling Language (UML). The application features online registration, doctor schedules, visit reminder notifications, and patient data management. This study concludes that the Android-based application can serve as an effective and efficient solution for improving health center services. Further development is recommended to enable integration with other healthcare systems.