<mets:mets OBJID="eprint_79983" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2026-11-13T13:18:16Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>Institutional Repository UIN Sunan Kalijaga Yogyakarta</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_79983_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>RANCANG BANGUN SISTEM PENYUSUNAN SOFTWARE REQUIREMENTS SPECIFICATION DENGAN DUKUNGAN LARGE LANGUAGE MODEL (LLM)</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">NIM.: 22106050011</mods:namePart><mods:namePart type="family">Firdy Dwi Aryani</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>Kualitas dokumen Software Requirements Specification (SRS) sangat menentukan keberhasilan proyek perangkat lunak, namun cacat kebutuhan seperti ambiguitas, ketidaklengkapan, dan inkonsistensi terminologi masih sering baru terdeteksi setelah dokumen selesai disusun. Tugas akhir ini bertujuan merancang dan membangun sistem berbasis web untuk mendukung penyusunan SRS secara terstruktur melalui integrasi tiga komponen, yaitu antarmuka berbasis formulir yang mengacu pada standar ISO/IEC/IEEE 29148:2018, bantuan Large Language Model (LLM) dengan pendekatan human-in-the-loop, serta mekanisme pemeriksaan kebutuhan berbasis indikator linguistik yang bekerja secara real-time selama proses penulisan berlangsung. Sistem dikembangkan menggunakan metodologi waterfall dan diuji melalui tiga jalur, yaitu pengujian fungsional (black-box testing), pengujian reliabilitas internal (automated testing), dan evaluasi ahli oleh tiga responden menggunakan kuesioner skala Likert. Hasil pengujian menunjukkan seluruh 15 skenario fungsional berhasil (100%), 518 dari 518 test case otomatis lulus (100%), dan evaluasi ahli memberikan skor rata-rata keseluruhan 4,06 dari 5,00 pada kategori Baik. Hasil ini membuktikan bahwa sistem mampu memandu penyusunan kebutuhan sesuai standar, memberikan saran perbaikan yang relevan tanpa menghilangkan kendali pengguna, serta mendeteksi cacat linguistik sejak dini, meskipun kejelasan panduan perbaikan pada panel umpan balik masih perlu ditingkatkan.</mods:abstract><mods:classification authority="lcc">004 Pemrosesan Data, Ilmu Komputer, Teknik Informatika</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2026-08-19</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></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_79983"><mets:rightsMD ID="rights_eprint_79983_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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