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bibo:abstract "The rapid growth of the modern software industry demands high-quality, consistent,\r\nand maintainable user interfaces (UI). Although Generative Artificial Intelligence (AI)\r\ntechnology has opened opportunities for automating UI code generation, the resulting code is\r\noften unstructured, difficult to maintain, and inconsistent with standardized component\r\ndevelopment patterns. This research aims to design and develop an Atomic Design-based UI\r\ngenerator system utilizing a Large Language Model (LLM) as its code generation engine. The\r\nsystem was developed using the Next.js framework, integrating frontend and backend layers\r\nwithin a unified framework, and utilizing the Google Gemini API as the LLM model. The\r\nAtomic Design approach was implemented through a layered prompt engineering technique\r\nthat explicitly embeds the Atom, Molecule, Organism, Template, and Page hierarchy\r\ninstructions into every prompt. The system supports three input modes Standard Prompt,\r\nTemplate Builder, and Structured Form to accommodate various user needs ranging from\r\ncreative exploration to controlled academic testing. Evaluation was conducted through output\r\ntesting and black-box testing across 12 functional scenarios. The results demonstrate that the\r\nsystem successfully generates UI components automatically in both HTML/Tailwind CSS and\r\nReact JSX formats, with consistent and modular structures aligned with Atomic Design\r\nstandards. All black-box testing scenarios achieved a Passed status. The layered prompt\r\nengineering mechanism proved effective in guiding the AI model to produce interface code that\r\nis consistent, modular, and compliant with Atomic Design principles."^^xsd:string;
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skos:prefLabel "005.36 Software Development / Pengembangan Perangkat Lunak" .
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dc:title "HTML Summary of #77223 \n\nRANCANG BANGUN SISTEM GENERATOR ANTARMUKA PENGGUNA BERBASIS ATOMIC DESIGN\n\n";
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foaf:familyName "Mufid Bahaudin Nugroho"^^xsd:string;
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