<mods:mods version="3.3" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mods:titleInfo><mods:title>RANCANG BANGUN SISTEM GENERATOR ANTARMUKA PENGGUNA BERBASIS ATOMIC DESIGN</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">NIM.: 22106050021</mods:namePart><mods:namePart type="family">Mufid Bahaudin Nugroho</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>The rapid growth of the modern software industry demands high-quality, consistent,&#13;
and maintainable user interfaces (UI). Although Generative Artificial Intelligence (AI)&#13;
technology has opened opportunities for automating UI code generation, the resulting code is&#13;
often unstructured, difficult to maintain, and inconsistent with standardized component&#13;
development patterns. This research aims to design and develop an Atomic Design-based UI&#13;
generator system utilizing a Large Language Model (LLM) as its code generation engine. The&#13;
system was developed using the Next.js framework, integrating frontend and backend layers&#13;
within a unified framework, and utilizing the Google Gemini API as the LLM model. The&#13;
Atomic Design approach was implemented through a layered prompt engineering technique&#13;
that explicitly embeds the Atom, Molecule, Organism, Template, and Page hierarchy&#13;
instructions into every prompt. The system supports three input modes Standard Prompt,&#13;
Template Builder, and Structured Form to accommodate various user needs ranging from&#13;
creative exploration to controlled academic testing. Evaluation was conducted through output&#13;
testing and black-box testing across 12 functional scenarios. The results demonstrate that the&#13;
system successfully generates UI components automatically in both HTML/Tailwind CSS and&#13;
React JSX formats, with consistent and modular structures aligned with Atomic Design&#13;
standards. All black-box testing scenarios achieved a Passed status. The layered prompt&#13;
engineering mechanism proved effective in guiding the AI model to produce interface code that&#13;
is consistent, modular, and compliant with Atomic Design principles.</mods:abstract><mods:classification authority="lcc">005.36 Software Development / Pengembangan Perangkat Lunak</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2026-06-04</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>UIN SUNAN KALIJAGA YOGYAKARTA;FAKULTAS SAINS DAN TEKNOLOGI</mods:publisher></mods:originInfo><mods:genre>Thesis</mods:genre></mods:mods>