Sep 2026· Jurnal Indonesia : Manajemen Informatika dan Komunikasi· 0 citations
TL;DR
The results of this study indicate that the Android-based digital library system with QR Code technology improves the speed and accuracy of book borrowing and returning processes through automatic data identification and facilitates the management of book, member, and transaction data.
Abstract
Library at MTsN 2 Kota Bekasi is one of the supporting facilities for learning activities that serves as a source of information for both students and teachers. The library provides various collections of textbooks and supplementary books to support the teaching and learning process. Therefore, proper library management is essential to ensure that services are delivered effectively, efficiently, and in accordance with the information needs of the school community. However, library management at MTsN 2 Kota Bekasi is still carried out manually, including recording book data, member data, and borrowing and returning transactions using logbooks. This condition results in inefficient management processes, increases the risk of recording errors, and makes data retrieval and report generation more difficult for librarians. Therefore, this study aims to design and develop an Android-based digital library system utilizing QR Code technology. The development method employed is the Software Development Life Cycle (SDLC) using the Waterfall model, which consists of requirements analysis, system design, implementation, and testing. The system was designed using Unified Modeling Language (UML), implemented using Android Studio, PHP, JavaScript, Visual Studio Code, and XAMPP, and tested using the Black Box Testing method to ensure that the system functions according to the specified requirements. The results of this study indicate that the Android-based digital library system with QR Code technology improves the speed and accuracy of book borrowing and returning processes through automatic data identification. The system also facilitates the management of book, member, and transaction data, reduces recording errors, and generates more structured and easily accessible reports. Therefore, the developed system is expected to enhance the effectiveness and efficiency of library services at MTsN 2 Kota Bekasi.
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James C. Davis, Kelechi G. Kalu, Huiyun Peng et al.· 1 citation
LLMs are increasingly used for code generation, yet they frequently hallucinate non-existent software packages, creating exploitable entry points into the software supply chain. We make four contributions to this problem. First, we show that prior evaluation methodologies systematically inflate hallucination rates by misclassifying standard-library modules as hallucinations in some languages. For Python, the overestimation reaches 9.4 percentage points. Second, we evaluate seven inference-time defenses for mitigating package hallucinations, including five guided decoding strategies (Greedy, Contrastive, DoLa, Nudging, and Active Layer-Contrastive Decoding), an iterative self-refinement approach (Self-Refine), and a Retrieval-Augmented Generation (RAG)-based defense.. Across eight models spanning five families and four programming languages (Python, JavaScript, Ruby, Rust), RAG reduces the package hallucination rate (PHR) in 18 of 32 model--language configurations. Third, we introduce Package Utility (PU) to assess whether defenses preserve valid and task-relevant recommendations. Among strategies evaluated, Greedy decoding provides the strongest average mitigation--utility trade-off. Fourth, we stress-test all strategies under adversarial prompts seeded with fabricated package names and find that PHR surges by up to 45 percentage points relative to standard prompts, with Ruby consistently the most vulnerable language (80.9--95.2\%). Under adversarial conditions, RAG and Self-Refine outperform all decoding-only strategies, indicating that robust defense requires either external grounding or iterative self-verification when prompts are actively hostile. Our results recast package hallucination as both a measurement problem and a decoding-time control problem, and they demonstrate that the choice of defense must be matched to the threat model and recommendation utility.
Albérick Euraste Djiré, Iyiola E. Olatunji, Melissa Tessa et al.· 1 citation
An audit-and-placebo protocol is proposed that separates verifier artifacts, interaction scaffolding, and grounded feedback credit in evaluations of self-evolving test generators in evaluations of self-evolving test generators.
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A diagnostic support system based on a unified web platform that classifies patients according to the risks of developing three diseases based on regularly collected clinical or audio data using classical supervised learning algorithms is presented.
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