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Indonesia masih menghadapi tantangan demografi berupa jumlah penduduk yang besar dengan laju pertumbuhan yang terus meningkat. Berdasarkan hasil Survei Demografi dan Kesehatan Indonesia (SDKI) tahun 2012, jumlah penduduk Indonesia mencapai sekitar 257 juta jiwa. Di sisi lain, penggunaan smartphone telah menjadi bagian dari kehidupan masyarakat, ditandai dengan peningkatan pengguna yang terus terjadi setiap tahun. Data dari Statista menunjukkan bahwa pada Oktober 2017, sekitar 75% pengguna smartphone di Indonesia menggunakan perangkat berbasis Android. Berdasarkan data integrasi Sistem Informasi Administrasi Kependudukan (SIAK) dengan KTP elektronik Kabupaten Tasikmalaya per Juni 2019, Kecamatan Cigalontang merupakan kecamatan dengan jumlah penduduk terbesar kedua setelah Karangnunggal, yaitu sebanyak 74.140 jiwa atau 4,14% dari total penduduk Kabupaten Tasikmalaya yang berjumlah 1.791.881 jiwa. Jumlah tersebut terdiri atas 37.998 laki-laki (4,17%) dan 36.142 perempuan (4,10%). Dalam program Keluarga Berencana (KB), metode kontrasepsi yang paling banyak digunakan adalah suntik 300 PUS sebesar 41,10% dan suntik 150 PUS sebesar 20,55%, dengan jumlah peserta aktif mencapai 506 akseptor atau sekitar 69% dari total 730 akseptor KB. Hasil Focus Group Discussion (FGD) bersama bidan dan akseptor KB menunjukkan masih sering terjadi keterlambatan maupun kelalaian dalam konsumsi pil KB serta jadwal kunjungan ulang suntik, sehingga diperlukan media atau sistem pengingat yang dapat membantu meningkatkan kepatuhan akseptor.  Penelitian ini dilakukan untuk menilai efektivitas aplikasi mobile “e-KABE” sebagai sarana pendukung pelayanan Keluarga Berencana di Desa Cigalontang, Kabupaten Tasikmalaya, pada tahun 2021.

Penelitian ini bertujuan mengembangkan aplikasi simulasi matematika dasar berbasis Android sebagai media pembelajaran interaktif bagi siswa sekolah dasar. Penelitian dilatarbelakangi oleh rendahnya keterlibatan siswa dan kesulitan siswa dalam memahami konsep aritmatika dasar melalui metode pembelajaran konvensional. Aplikasi dirancang dengan mengintegrasikan modul latihan, permainan edukatif dengan tingkat kesulitan bertahap, serta sistem penghargaan berbasis pencapaian untuk meningkatkan motivasi dan minat belajar siswa. Proses pengembangan menggunakan metode Waterfall yang meliputi tahapan analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan penerapan aplikasi. Pengembangan aplikasi dilakukan menggunakan Android Studio dan bahasa pemrograman Java, sedangkan SQLite digunakan sebagai media penyimpanan data lokal. Validasi fungsional dilakukan melalui Black Box Testing untuk memastikan seluruh fitur aplikasi berjalan sesuai kebutuhan sistem. Siswa sekolah dasar dilibatkan sebagai responden untuk mengevaluasi tingkat kegunaan dan kesesuaian aplikasi sebagai media pembelajaran. Hasil penelitian menunjukkan bahwa aplikasi dapat berfungsi dengan baik pada perangkat Android serta memberikan kontribusi positif dalam meningkatkan pemahaman aritmatika dan motivasi belajar siswa.

Kesadaran dan kepedulian masyarakat terhadap lingkungan telah mendorong munculnya berbagai inisiatif pengelolaan sampah berbasis komunitas, salah satunya melalui mekanisme bank sampah. Namun pada praktiknya, banyak bank sampah masih mengandalkan pencatatan manual yang berpotensi menimbulkan kesalahan pencatatan, duplikasi data, keterlambatan pelaporan, dan kesulitan pelacakan transaksi. Penelitian ini bertujuan untuk mengembangkan sistem digital pengelolaan bank sampah berbasis mobile android dengan memanfaatkan Low-Code Development Platform (LCDP) sebagai pendekatan pengembangan yang efisien dan ekonomis. Hal ini sejalan dengan harapan pengelola bank sampah terkait penghematan biaya pengembangan, operasional, dan biaya perawatan sistem. Metode Prototyping digunakan sebagai model pengembangan sistem, dimana proses iterasi dilakukan berdasarkan umpan balik pengguna hingga sistem sesuai dengan kebutuhan operasional. Selama fase konstruksi, purwarupa yang dibangun mengalami dua tahap penyempurnaan sebagai hasil evaluasi pengguna terhadap perluasan fitur dan peningkatan fungsionalitas sistem. Evaluasi sistem dilakukan dengan menguji fungsionalitas setiap fitur menggunakan metode uji blackbox, melibatkan dua responden dengan perangkat yang berbeda. Hasil pengujian menunjukkan konsistensi hasil uji untuk setiap responden, seluruh fungsi sistem, termasuk pencatatan transaksi penukaran barang dan penarikan saldo, pengelolaan data peserta, autentikasi pengguna, serta pembatasan hak akses berjalan sesuai dengan perencanaan tanpa ditemui kendala fungsional. Pemanfaatan LCDP dengan metode prototyping memberikan kemudahan dan mempercepat proses pengembangan sistem serta memberikan fleksibilitas adaptasi dalam merespons perubahan maupun penambahan kebutuhan fungsionalitas sistem.

Mental health issues among university students have become a growing concern, driven by academic pressures, career uncertainties, and complex social transitions. However, a large proportion of students remains reluctant to seek professional psychological support due to social stigma and limited access to institutional counseling services. This study proposes the design and implementation of an Android-based chatbot application that integrates mood tracking and sentiment analysis to continuously monitor the emotional states of university students. The system employs a fine-tuned RoBERTa (Robustly Optimized BERT Pretraining Approach) model trained on the EmoContext conversational dataset (SemEval-2019 Task 3), comprising 30,160 labeled three-turn dialogue instances across four emotion classes: angry, happy, sad, and others. The model was fine-tuned for four epochs using the AdamW optimizer with a learning rate of 2e-5 and a maximum sequence length of 128 tokens. Evaluation on a held-out validation set of 6,032 samples yielded an overall accuracy of 88.28%, a macro-average F1-score of 0.87, and a weighted-average F1-score of 0.88. Per-class F1-scores were 0.89 (angry), 0.83 (happy), 0.91 (others), and 0.86 (sad). The classified emotion is transmitted in real time to the chatbot response logic, which generates empathetic replies and personalized relaxation recommendations based on the detected mood. Primary data collection through questionnaires and interviews with 62 and 19 university students respectively confirmed the need for accessible digital mental health support. The results demonstrate that RoBERTa-based fine-tuning on conversational data provides a reliable foundation for real-time emotion-aware mental health chatbot systems.

This study aims to design and develop an Augmented Reality (AR)-based application for real-time data monitoring of an automatic weather station at PT. XYZ. The system was developed using a prototyping method, involving five key stages: sensor data acquisition via CBOX devices and the Modbus RTU protocol, data transmission through a Flask-based Web API, storage in a MySQL database, QR code-based target image creation using the Vuforia Engine, and a 3D visualization interface developed with Unity integrated with the Vuforia SDK on Android devices. The system successfully received and stored weather data—such as temperature, humidity, and wind speed—into the MySQL database. The AR application also displayed a stable 3D interface panel over QR code markers, providing real-time data updates through an HTTP-based mechanism. This research demonstrates the successful integration of SCADA, Flask, MySQL, and Unity, enhancing both the functionality and commercial appeal of PT. XYZ’s weather station products. Future research should focus on field testing, cloud network integration, and device compatibility.

The development of information technology, particularly the use of smartphones, has changed human activity patterns and significantly impacted the education sector. The "one-stop-shop" concept reflects the use of mobile devices as centers for various activities, including learning. This situation drives the need for innovation in the development of adaptive and interactive learning media. One solution that can be developed is an Android-based mobile application using Flutter, which can increase the effectiveness and efficiency of the learning process. The Association of Multimedia and Information Technology Professionals (PPMultindo), an organization focused on technology, has developed an Android-based learning platform. This platform is designed to provide flexible access to materials, support interactivity, and facilitate collaboration between educators. Features such as learning analysis, material recommendations, and automatic evaluation are expected to improve the quality of the learning experience. However, the implementation of this technology still faces various challenges, including limited technological competence of educators, inadequate infrastructure, and adjustments to curriculum needs. Therefore, collaborative efforts are needed to optimize the use of mobile technology to support educational transformation in the digital era.

The rapid development of information technology has had a significant impact on the world of education, particularly in the use of mobile applications as learning media. Developing Android-based applications using Flutter is one innovation that can increase efficiency and provide a more personalized and adaptive learning experience. In this context, educators are required to continue innovating to meet the increasingly diverse and dynamic needs of students in the digital era. The Multimedia and Information Technology Professional Association (PPMultindo), an organization that brings together technology professionals, is taking advantage of this opportunity by developing an Android-based learning platform. This platform is designed to provide easier, more flexible, and more interactive access to learning materials, as well as support the process of designing more engaging materials. Features such as learning data analysis, material recommendations, and automatic evaluation are expected to increase the effectiveness and efficiency of the teaching and learning process, while also providing a means for collaboration between members. However, the implementation of this technology still faces various challenges, such as limited technological competence of educators, inadequate infrastructure, and the need for curriculum adjustments. Therefore, collaborative efforts are needed to optimize the use of mobile technology to support educational transformation.

The limited use of interactive learning media has made it difficult for students to visualize the functions and assembly flow of computer components. This study aims to design and develop an Android-based educational game called “Assemble & Learn” as an interactive medium for computer assembly lessons, specifically for vocational high school students at SMK Negeri 1 Tanjung Jabung Barat. The development process follows the Multimedia Development Life Cycle (MDLC), which includes the stages of concept, design, material collection, assembly, testing, and distribution. The learning content covers several core competencies: KD 3.2/4.2 on computer assembly, KD 3.3/4.3 on assembly testing, KD 3.4/4.4 on BIOS configuration, and KD 3.5/4.5 on operating system installation, with a focus on KD 3.2 and KD 3.5. Research instruments consist of validation questionnaires for subject-matter experts, media experts, and student trials using the System Usability Scale (SUS). Validation results show that the educational game received an average score of 94% from media experts and 100% from subject-matter experts, both categorized as “Highly Feasible.” Meanwhile, student trials indicated strong acceptance, with an average SUS score of 85% (excellent usability). In conclusion, the “Assemble & Learn” educational game offers an innovative solution to boost learning motivation, simplify material visualization, and provide flexible practice opportunities, thereby supporting the achievement of computer assembly competencies in an optimal and effective way.

The limited availability of integrated digital tourism information in Blitar Raya has made it challenging for visitors to plan their travel routes efficiently. This research aims to develop an Android-based Geographic Information System (GIS) that integrates the Google Maps API with the Bellman-Ford algorithm to optimize the shortest travel routes among tourism destinations. The system was developed using the Rapid Application Development (RAD) methodology, emphasizing user involvement through iterative prototyping and feedback. Primary data were collected from field observations, semi-structured interviews with tourists and local administrators, and beta testing involving 52 respondents, while secondary data were obtained from the Blitar Tourism Board and BPS statistical databases. The implementation integrates the Google Distance Matrix API to construct a weighted graph, which is processed by the Bellman-Ford algorithm, demonstrating higher route stability and accuracy than the Dijkstra and Haversine approaches in small-to-medium graph structures. The system achieved an 84.46% user acceptance rate, categorized as “Excellent” according to the ISO/IEC 25010 usability standard. Empirical findings show that the average response time of 1.5–2.5 seconds indicates high computational efficiency for real-time map rendering. This study contributes theoretically by presenting an algorithmic integration framework for mobile GIS applications and practically by offering a functional digital tourism platform to enhance local tourism management. The findings also suggest that combining RAD with algorithmic optimization can effectively bridge the gap between user experience and computational performance in tourism-based GIS systems.

The development of digital technology in recent years has had a significant impact on almost all sectors, especially the financial sector. Digitalization is no longer an option but a fundamental necessity for financial institutions, including Savings and Loan Cooperatives (KSP), to remain competitive and capable of providing efficient, accurate, and high-quality services. The need for technology that can improve service processes, data management, and transactions has become increasingly urgent amid the growing complexity of cooperative members’ demands and the increasing competition among financial institutions.This study aims to analyze the transformation of financial services at KSP Credit Union Bahtera Sejahtera through the implementation of the Escete Program, an online-based digital system. Before 2019, this cooperative used the SIKOPDIT CS system which operated offline, resulting in difficulties in data synchronization and service efficiency. The method used in this study is a qualitative descriptive approach using the perspective of Institutional Theory to examine the motivations behind organizational change.The results of the study indicate that the transition from SIKOPDIT CS to the Escete Program is not merely a technical change but also a form of organizational adaptation to three institutional pressures: (1) Coercive Pressure arising from regulations requiring financial transparency; (2) Mimetic Pressure as an effort to emulate the success of banking digitalization; and (3) Normative Pressure to meet members’ expectations and the professionalism of human resources. The implementation of the Escete Program has proven to improve real-time data accuracy, accelerate services through Android integration, and transform the organizational work culture into a more modern and transparent one.

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.

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.

The increasing popularity of futsal in Jayapura City has created a growing demand for efficient access to information regarding available sports facilities. However, the lack of an integrated digital platform leads to inefficiencies in locating and booking futsal fields, often forcing users to rely on manual communication or generic navigation services that lack real-time data. This study aims to develop an Android-based application that optimizes the search for the nearest futsal field using the Greedy Algorithm (GA). The system integrates the Google Maps API, the Firebase Realtime Database, and Kotlin/Java to provide real-time field availability, route visualization, and online booking features. The research employed the Waterfall development model, with data collected through observation, interviews, and a literature review, involving 19 futsal fields in Jayapura City. System testing was conducted using Black-Box Testing and User Acceptance Testing (UAT). The results show that implementing the Greedy Algorithm increased route efficiency by 22%, reduced search time by 55%, and achieved 93.2% user satisfaction. All core functions passed functionality testing without errors. This study contributes both practically and theoretically by demonstrating the potential of heuristic-based optimization in sports facility management and promoting smart-city digitalization in urban sports infrastructure.

  Abstract. This study aims to develop and evaluate an artificial intelligence–based expert system to support fault diagnosis in Air Handling Units (AHUs). Early fault identification in AHU systems is often constrained by reliance on technician experience, which may lead to inconsistent diagnostic outcomes. The proposed system is intended to provide a consistent, explainable, and practical decision-support tool to assist maintenance personnel, particularly less-experienced technicians, in identifying AHU faults accurately. Methodology: The research adopts a rule-based expert system approach using forward chaining inference. Knowledge acquisition was conducted through structured interviews with experienced HVAC technicians and supported by technical documentation. The resulting knowledge base consists of observable symptoms, diagnostic rules, and corresponding corrective actions. The system was implemented as an Android-based mobile application to enable direct field usage. System validation was performed using real operational fault scenarios, with expert diagnoses serving as the reference standard. Findings: Evaluation results indicate full agreement between the system-generated diagnoses and expert assessments across all tested scenarios. This demonstrates that the proposed system is capable of producing accurate and consistent diagnostic outcomes within its defined knowledge domain. Implications: The system operates using deterministic rules without incorporating uncertainty modeling or probabilistic reasoning. Additionally, validation was limited to a finite number of real-world scenarios, which may affect generalizability to broader AHU configurations. Practical implications: The expert system can be utilized as a practical diagnostic aid in routine AHU maintenance, improving response time, diagnostic consistency, and technician training effectiveness. Originality: This study contributes a mobile-based, explainable expert system specifically tailored for AHU fault diagnosis, emphasizing practical deployment and rule transparency rather than data-intensive learning models.

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.