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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.

River pollution has become one of the serious environmental issues in Indonesia, including in the Gelis River in Kudus City. The lack of public awareness—especially among the younger generation—in maintaining river cleanliness highlights the need for effective and engaging educational media. This study aims to design an Android-based educational game as an interactive learning tool for children aged 7 to 12 years to raise their awareness about the importance of keeping rivers clean. The research method used is Research and Development (R&D), employing the ADDIE development model (Analysis, Design, Development, Implementation, Evaluation). The game developed, titled RiverCourse: Petualangan Menjaga Sungai (RiverCourse: The Adventure of Protecting the River), features a sidescrolling mechanic with a visual style combining pixel art and cartoons, suited to the cognitive development stage of children. Testing was conducted on the target age group through observation and simple questionnaires.

Learning Hajj rituals requires innovation to overcome the limitations of available media, one of which is through the utilization of the integration of the Android platform with Augmented Reality technology. The Muslim Sadiq application on smartphones displays 3D objects related to the practice of Hajj rituals. This study aims to explain the design of interactive media based on Augmented Reality as an innovation in learning Hajj rituals, expected to improve student understanding through a more visual, interactive, and contextual learning experience. This media design method adopts two stages of the ADDIE model (Analysis, Design, Development, Implementation, Evaluation), namely the needs analysis and media design stages. This study reveals that learning Hajj rituals requires interactive and applicable media to overcome the gap between theoretical understanding and the practice of Hajj worship in real life. The designed media utilizes AR technology to create a simulation of Hajj implementation and supports experience-based learning. Although the design has considered technical and pedagogical aspects, this media is still in the design stage and has not been tested or implemented directly. Therefore, further research is needed to assess the effectiveness of this media in learning Hajj rituals.

Android continues to innovate, and biometric systems particularly fingerprint sensors must operate with high efficiency. However, the main challenge lies in the communication between hardware and software, which often causes high latency, excessive power consumption, and protocol incompatibility between components. As a result, authentication speed decreases and system stability is compromised, especially on mid- to low-range devices. This study explores various implementations of Android-based fingerprint systems, focusing on how sensor modules interact with the microcontroller or Trusted Execution Environment (TEE) and the operating system through a hardware-software co-design approach to evaluate integration efficiency across all layers. The analysis reveals that conventional protocols such as Bluetooth or serial connections still cause delays, while improvements in drivers and the Hardware Abstraction Layer (HAL) can significantly reduce latency. As a solution, the researchers propose a co-design optimization approach that utilizes data flow normalization within the HAL and adopts lightweight communication protocols to accelerate the verification process. Based on the test results, this approach successfully improves efficiency—authentication time is reduced by up to 35% and power consumption decreases by approximately 15%. Therefore, the efficiency of communication between hardware and software becomes a key factor in enhancing the performance and reliability of fingerprint systems on Android devices.

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.

Penelitian ini bertujuan untuk merancang dan membuat interface komunikasi data antara Electronic Control Unit (ECU) sepeda motor dengan sistem Android. Masalah yang dihadapi oleh bengkel rumahan seperti Ngoprek Garage Motoshop adalah keterbatasan alat untuk mendeteksi kerusakan ECU secara otomatis. Penelitian ini menggunakan mikrokontroler ESP32 sebagai penghubung antara ECU dan aplikasi Android, yang dirancang menggunakan MIT App Inventor. Sistem ini mampu membaca data kesalahan (Diagnostic Trouble Code/DTC) dari ECU dan menampilkannya secara langsung pada aplikasi Android. Metode penelitian yang digunakan mencakup perancangan perangkat keras dan perangkat lunak, serta pengujian sistem terhadap sepeda motor Honda. Hasil menunjukkan bahwa sistem ini mampu membaca dan menampilkan kode DTC dengan akurasi yang cukup tinggi, meskipun terdapat keterbatasan pada pembacaan parameter data secara real-time. Sistem ini diharapkan menjadi solusi alternatif bagi bengkel kecil dalam melakukan diagnosa awal terhadap kerusakan ECU.  

This research stems from the problem of manual book lending management in libraries, which often leads to obstacles such as delays in recording, data errors, and difficulties in monitoring collections. The main objective of this research is to design and develop a web-based library information system that can facilitate member data management, borrowing, and returning, as well as providing real-time book availability information. The method used is software development with a structured approach, through the stages of needs analysis, design, implementation, and testing with black box testing. The results of the study indicate that the system built is able to meet user needs, as evidenced by the successful testing that carried out all main functions without errors. The implications of this research are increased efficiency in library management and ease for students in borrowing and checking book availability. However, this research still has limitations in advanced features such as integration with the attendance system or automatic fine payments, so that these can be developed in future research.

The development of information technology has encouraged institutions, including hospitals, to adopt digital systems to improve operational efficiency. One important aspect is the employee attendance system, which previously relied on fingerprints. This method has limitations, such as difficulty detecting when fingers are not in ideal condition and causing queues during peak hours. This research aims to design and implement an Android-based attendance system using the Eigenface facial recognition method as a faster, safer, and more accurate alternative. Eigenface works by extracting facial features using Principal Component Analysis (PCA), thus being able to efficiently recognize individual identities. The system was developed with MySQL database integration and tested on employees of Khalishah General Hospital. The implementation results showed that the system can recognize faces with a good level of accuracy and increase the effectiveness of attendance recording. Furthermore, the use of facial-based attendance can minimize the potential for fraud and increase user comfort because it does not require physical contact. Thus, the Eigenface method has proven feasible to be implemented as a modern attendance solution to support employee attendance management in hospital work environments and other institutions.

The digitalization of learning media in the world of education is increasingly visible. The aim of this research is to analyze the strengthening of Citizenship Education learning through learning media. This research uses a qualitative research method with a literature study approach. Citizenship education is an important thing to study in order to understand how citizens carry out their roles, rights and responsibilities for the country. There are various studies that have proven the effectiveness of several learning media for PPKn, including Powtoon, Anchor Podcast, Android Applications, and Roleplay.

The development of digital media and innovative learning models in Junior High School Science education reflects a sustained commitment to meeting the demands of 21st-century skills and improving the quality of science instruction. A comprehensive literature review (2019–2024) reveals the dominance of the Research and Development (R&D) approach, which consistently yields highly valid, practical, and effective digital resources, such as Augmented Reality (AR), Android-based applications, and interactive educational games. These digital tools are synergistically integrated with modern instructional models, including Problem-Based Learning (PBL), Inquiry-Based Learning (IBL), and Predict-Observe-Explain (POE), which are proven effective in increasing student engagement, enhancing cognitive outcomes, and honing essential competencies such as Science Process Skills (SPS) and Higher-Order Thinking Skills (HOTS). Ultimately, this integration contributes significantly to overcoming learning difficulties in complex and abstract Science topics (e.g., the human digestive system) while also effectively addressing contemporary educational challenges, fostering meaningful learning experiences, and supporting long-term academic success for students.

The purpose of this study is to analyze the potential and development strategies of the historical tourism site “Jejak Bung Karno” (The Footsteps of Bung Karno) in Ende Regency, as well as to design an Android-based digital media to enhance the overall visitor experience. Ende is recognized for its profound historical value as the place where the foundational ideas of Pancasila were first conceived, and it is home to several important sites such as the Bung Karno Exile House and the Pancasila Reflection Park. However, the management of this destination remains suboptimal, particularly in terms of promotion, the application of digital technology, and the delivery of engaging tourist information. The user interface design was developed using Figma software, while user experience testing was conducted through the User Experience Questionnaire (UEQ) involving 35 participants. The results indicate that the Attractiveness (2.027) and Perspicuity (3.804) aspects received “excellent” ratings, while Efficiency, Dependability, Stimulation, and Novelty were categorized as “above average.” These findings suggest that the application interface design aligns well with user needs and preferences. Furthermore, the study highlights that the implementation of Android-based technology contributes positively to the digitalization of historical tourism, broadens promotional reach, and strengthens the identity of “Ende Bumi Pancasila” as an educational and cultural tourism destination in the era of digital transformation.

The waste detection application is a solution to identify and classify waste. With the increasing waste problem, this application aims to assist in classifying waste into organic, inorganic, and unknown categories. This research implements a waste detection application that runs on smartphones with the Android operating system. The application is the result of a capstone project from the Bangkit program in the MSIB batch 6. The development of this application is divided into several parts, namely backend, frontend, and deployment. The author focuses on the deployment process of the application using Google Cloud Platform. The Google Cloud Platform infrastructure was chosen due to its scalability and flexibility. The services utilized include Google Compute Engine (GCE), Google Virtual Private Cloud (VPC), and Google Cloud Storage (GCS). The deployment process involves creating a new project in Google Cloud, configuring virtual machines, and setting up Google Cloud Storage. The server VM configuration includes the installation of SQL Server (MariaDB), deployment of the Machine Learning API, and Backend API. Testing was carried out on the Machine Learning API using Postman and the Backend API through a browser. The results show that Google Cloud Platform can be implemented as a cloud computing infrastructure for waste detection applications. The Machine Learning API is able to read objects in the form of images sent by users.

The purpose of this study was to develop and test a mathematics learning tool using Virtual Reality (VR) technology on the Android platform. The material focused on is flat-sided spatial objects for junior high school students. The development stages were carried out through various steps, from planning to testing on students. The findings showed that the media was considered appropriate by experts, easily accessible to students, and contributed to improving learning outcomes. In addition, students appeared more enthusiastic and excited during the learning process. A review of two other articles confirmed that VR and AR-based media were able to improve understanding and make learning more enjoyable. This tool could be an interesting alternative for teaching mathematics.

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.

This research aims to develop an Augmented Reality (AR) application as a navigation aid and facility introduction tool in the Informatics Engineering Building of Bengkalis State Polytechnic. This application is specifically designed to help new students and visitors understand and navigate the complex campus environment. By utilizing AR technology, the application provides an interactive guide that displays routes to various laboratories and presents detailed information about available facilities. The method used in developing this application is the Multimedia Development Life Cycle (MDLC), which consists of five stages: planning, design, development, testing, and launch. In the planning stage, a user needs analysis is conducted to ensure that the developed application meets the expectations and needs of end users. The design stage includes the creation of user interaction flows and visual interfaces, while the development stage involves the integration of AR technology with location data and campus facility information. Testing is conducted to ensure the functionality and accuracy of the navigation features and the quality of the user experience before the application is launched. The results of this study indicate that the AR application is able to provide a more interactive and informative experience than conventional media. New students and visitors can easily find laboratory locations and obtain a clear overview of campus facilities. In addition to improving navigation efficiency, this application also supports the adoption of digital technology in the campus environment. Thus, this research not only contributes in terms of ease of access to information, but also encourages the use of AR technology in the world of education, especially at Bengkalis State Polytechnic.

A wedding is an important event in a person's life that requires various careful preparations, one of which is sending invitations to guests. This research aims to create an Android-based wedding invitation booking application that utilizes Augmented Reality (AR) technology with a Design Thinking approach. This approach includes five main stages, namely empathize, define, ideate, prototype, and testing, to ensure that the developed application is truly in accordance with the needs and expectations of users. With AR technology, users can view and interact directly with virtual invitations through digital devices such as smartphones, which provides a more engaging, interactive, and modern visual experience than conventional physical invitations. The app's key features include invitation design selection, content customization (name, location, date, and couple's photo), as well as simulated invitation display with three-dimensional effects via AR. The app also allows users to store, share, and place orders directly through an integrated system. The results of the evaluation conducted using the System Usability Scale (SUS) method showed a score of 75.3. This score indicates that the app has a good usability level and is positively received by the majority of respondents. In addition, this application is considered to be able to increase efficiency in the invitation ordering process and provide a more modern and personal impression to users and invited guests. The conclusion of this study is that AR-based wedding invitation booking apps not only serve as a practical tool, but also become digital innovations that enrich the user experience in modern weddings. This research is expected to make a real contribution to the development of creative information technology and inspire other developers to create similar solutions that are innovative, efficient, and relevant to the needs of the times.

This research focuses on the development of an Android-based vegetable detection application by utilizing digital image processing technology and data communication through Application Programming Interface (API). This application is designed to make it easier for users to visually recognize different types of vegetables using the device's camera. The detection process is carried out by sending the image to a cloud server, where the image analysis process is carried out to identify the type of vegetable, displaying its name, characteristics, and benefits. The app's implementation includes an intuitive and user-friendly user interface, with key features such as login, registration, and an interactive dashboard. The dashboard displays user information, location, ambient temperature, vegetable detection history, and direct access to the camera for real-time detection processes. The utilization of cloud computing technology not only keeps application performance lightweight and responsive, but also enables high processing efficiency and data scalability. This allows the application to continue to evolve according to the increasing number of users and incoming data. Image processing is done with machine learning algorithms that are trained to recognize the shape, color, and texture of different types of local vegetables. In addition, this system is also equipped with a periodic data update feature to be able to adjust to the development of new vegetable classifications. The test results show that the app is able to recognize different types of vegetables with a high level of accuracy, as well as provide additional relevant information quickly and accurately. Tests are carried out on a variety of lighting and background conditions to ensure the reliability of the system. The success of the development of this application reflects the integration of modern technology in supporting the digital agriculture sector.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring. 

Kemajuan teknologi telah menciptakan peluang baru dalam bidang pendidikan, terutama bagi anak usia dini. Penelitian ini mengembangkan sebuah game edukatif berbasis Android yang ditujukan untuk anak berusia 4 hingga 6 tahun, dengan materi pengenalan huruf, angka, buah, dan hewan. Pengembangan aplikasi ini menggunakan model Waterfall yang mencakup analisis kebutuhan, perancangan, implementasi, pengujian, serta pemeliharaan. Game dirancang menggunakan Flutter dan bahasa Dart untuk menghasilkan tampilan yang interaktif dan responsif, serta dilengkapi dengan fitur audio-visual yang menarik. Berdasarkan hasil pengujian Blackbox dan User Acceptance Testing (UAT), sebanyak 87% anak menunjukkan ketertarikan terhadap game ini, dan 82% mampu mengingat materi yang disampaikan. Para guru juga memberikan respon positif, menilai permainan ini efektif sebagai media pembelajaran. Meski demikian, masih diperlukan penambahan variasi soal serta peningkatan kinerja aplikasi guna meningkatkan pengalaman pengguna secara keseluruhan.