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Indramayu mango is a seasonal fruit that is highly favored due to its delicious taste and high nutritional content. However, high mango production is often not supported by adequate post-harvest facilities, particularly in terms of fruit ripeness classification. Currently, mango ripeness classification is still performed manually, which tends to be subjective and inconsistent. To address this issue, this study proposes a ripeness detection system for Indramayu mangoes by integrating the TGS2602 gas sensor and the YOLOv11 algorithm based on image processing. The TGS2602 sensor is used to detect ethylene gas emitted by ripe mangoes, while YOLOv11 is employed for visual image analysis of the fruit. This study aims to evaluate the system’s performance in classifying ripe and unripe mangoes, as well as analyze the integration between the gas sensor and the object detection model. The test results show that the TGS2602 sensor can detect increased ethylene gas concentration in ripe mangoes, while YOLOv11 demonstrates high accuracy in detecting mangoes based on visual images, with precision and recall close to 1.0. The system was also tested under various lighting conditions, including dark environments, and still performed well, although with a slight decrease in accuracy under low-light conditions.

Learning to read the Al-Qur'an at TPA Al-Amin Brahu Ponorogo still relies on conventional methods, which lead to low motivation and boredom among students. This study aims to design and develop interactive learning media based on Augmented Reality (AR) through the AR-Iqro' Jilid 5 application on the Android platform. The development method employed is the System Development Life Cycle (SDLC) using the Waterfall model, which encompasses the stages of planning, design, implementation, testing, and maintenance.The results of the study indicate that the application performs exceptionally well, with material validation reaching 96%, media design at 96%, and user testing at 97%. These findings prove that the AR-Iqro' Jilid 5 application is highly feasible for use due to its ease of navigation and intuitive visual interface. The implication of this research is the availability of an innovative alternative learning medium capable of increasing students' interest in learning the Al-Qur'an, with the potential for broader implementation in technology-based Islamic educational institutions.

This study aims to analyze the performance of Android-based attendance applications used at PT PLN ULP West Sumba by integrating two evaluation methods, namely WebQual 4.0 and Importance Performance Analysis (IPA). This attendance application functions to monitor employee attendance digitally so that it is expected to be able to improve the efficiency and accuracy of data recording. Evaluations are conducted to assess the extent to which the application meets the needs of users as well as the expected performance. WebQual 4.0 is used to measure the quality of user experience in terms of ease of access, interactivity, trust, and satisfaction, while IPA is used to compare the level of user interest with application performance based on four main attributes: system quality, information quality, service quality, and usage quality. The research data was collected through a survey with questionnaires compiled according to WebQual 4.0 and IPA indicators, involving application users at PT PLN ULP West Sumba. The results show that the majority of users are satisfied with the ease of use and performance of the application, but there are aspects that need to be improved, especially the speed of the system and a more user-friendly interface design. The science analysis emphasizes that the quality of systems and information is a crucial factor that must be a priority for development. This research provides strategic recommendations for PT PLN ULP West Sumba to improve the performance of the attendance application and support the company's operational needs in a sustainable manner.

The aim of the research is to find out the process of developing knowledge learning media based on Android applications.Learning media is very much needed as a tool used in practical learning.Changes in educational progress require innovation in learning media to keep them up to dat and able to overcome new problems that arise. The research method used is the R & D research and development method with the 4D model. The stages of the 4D development model are 1) Definition; 2) Design; 3) Development; 4) Distribution. This research produces android-based textile knowledge learning media. The software used is iSpring Suite Toolkit Authoring based on Power Point; and Website 2 APK Builder.The iSpring Suit software is used in the design and development of learning media, while the Website 2 APK Builder software is used to change Android application programs. Based on the results of the learning media feasibility questionnaire, it can be seen that the textile knowledge learning media is very feasible to use, reaching 90%.

This study addresses the problem of how the implementation of HOTS-based Android gamification influences the higher-order thinking skills of students with ADHD, a group that often faces challenges in traditional learning environments. A quantitative experimental research design was applied, involving 26 students with ADHD from four special needs schools (SLBs) in West Kalimantan. The intervention included HOTS-oriented Android gamified learning, and students' performance was measured using pre-tests and post-tests based on HOTS-level questions. The average pre-test score was 23.72, while the post-test score increased to 53.21. A paired sample t-test showed a significant improvement (t = 8.688 > t_table = 1.708, at a 5% significance level). However, only 57.69% of students met the minimum mastery criteria (KKM = 67), indicating that 15 out of 26 students achieved the expected learning standard. The implementation of HOTS-based Android gamification significantly improved the higher-order thinking skills of students with ADHD. Nonetheless, the overall results, based on average scores and classical completeness, indicate that many students still did not reach the expected level of mastery. Further enhancements in instructional design may be necessary to optimize outcomes for this group of learners.

This study presents a comprehensive comparative analysis of four traditional machine learning algorithms Decision Tree, Random Forest, K-Nearest Neighbors, and Support Vector Machine for Android malware detection using the preprocessed TUANDROMD dataset comprising 4,465 instances and 241 features representing both static and dynamic application characteristics. Motivated by the limitations of conventional signature-based and hybrid detection methods, especially in managing imbalanced datasets and detecting emerging malware variants, the study employed SMOTE to ensure balanced training data and fair model evaluation. The dataset was divided into 80% training and 20% testing subsets, and models were assessed using key performance metrics including accuracy, precision, recall, F1-score, and ROC AUC. The findings revealed that the proposed Random Forest model outperformed the other classifiers, achieving an accuracy of 0.993, precision of 0.992, recall of 1.000, F1-score of 0.996, and a near-perfect ROC AUC of 0.9998 surpassing state-of-the-art approaches. These results affirm the superior predictive capability, consistency, and robustness of the Random Forest algorithm in Android malware detection. The study concludes that base models, when integrated with class-balancing techniques, provide reliable and efficient malware detection across imbalanced datasets. For future research, the study recommends exploring advanced hybrid or ensemble frameworks that integrate Random Forest with deep learning architectures or other meta-heuristic optimization techniques to further enhance detection accuracy, adaptability, and resilience against rapidly evolving Android malware threats.

Despite its cultural potential, Wetabar Village has not been supported by effective digital promotional media. Information access remains limited, and the lack of interactive promotional platforms has contributed to the low interest of tourists. Current promotional efforts rely heavily on conventional methods, resulting in decreased visitor numbers. The implementation of digital technologies such as Augmented Reality (AR) and Web-based 360° Virtual Reality Tours is considered an effective approach to increasing tourist engagement by offering immersive exploration experiences and interactive cultural content. This research aims to design and implement a web-based tourism promotion media that integrates local cultural content with AR and 360° virtual tour technologies. The development process follows the MDLC research method, utilizing the Lumi H5P platform and PHP for system implementation. The resulting system enables users to digitally explore Wetabar Village through panoramic views and interactive multimedia features. The findings show that the developed application runs smoothly on both Android devices and laptops and is capable of providing hotspot access to operate the virtual reality features. This innovation is expected to enhance tourist interest while supporting cultural preservation and promoting digital transformation within the tourism sector of West Sumba.

The advancement of information technology has had a significant impact across various sectors, including healthcare. The digitalization of healthcare services has become a solution to improve efficiency, effectiveness, and accessibility for the public. Puskesmas Selindung still uses a manual patient registration system, which leads to several issues such as long queues, extended waiting times, and the risk of lost or damaged patient records. Based on visit data, the number of patients coming to Puskesmas Selindung has increased each year. Therefore, a digital queue system is needed to optimize the patient registration process. This research aims to analyze and design an Android-based patient registration queue application to improve service efficiency at Puskesmas Selindung. The research methods include system requirements analysis, user interface design, and the development of core features to support the online patient registration process. The implementation of this application is expected to reduce long queues, speed up administrative processes, and make it easier for patients to access healthcare services more effectively and accurately. With this Android-based system, the quality of healthcare services at Puskesmas Selindung is expected to improve significantly.

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.

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 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.

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.