<mets:mets OBJID="eprint_32198" 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="2026-07-21T07:17:39Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>EPrints Universitas Amikom Yogyakarta</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_32198_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>PENGEMBANGAN CHATBOT HUKUM INDONESIA&#13;
BERBASIS RAG DENGAN EVALUASI KINERJA&#13;
RETRIEVAL DAN KONSISTENSI FAKTUAL</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">Aan Triya</mods:namePart><mods:namePart type="family">Vinanta</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>Rendahnya pengetahuan hukum masyarakat Indonesia sering kali&#13;
menyebabkan kesulitan dalam mencari rujukan pasal yang tepat, yang berujung&#13;
pada keputusan keliru dan ketidakmerataan akses keadilan, sementara penggunaan&#13;
Large Language Model (LLM) murni berisiko tinggi menghasilkan halusinasi&#13;
tanpa sumber rujukan eksplisit. Penelitian ini bertujuan mengatasi permasalahan&#13;
tersebut dengan mengembangkan chatbot hukum menggunakan metode RetrievalAugmented&#13;
&#13;
Generation (RAG) yang memproses delapan Undang-Undang utama&#13;
melalui teknik recursive chunking dan menyimpannya dalam Qdrant Vector&#13;
Database. Sistem menggabungkan pencarian semantik dan leksikal yang&#13;
disempurnakan dengan mekanisme reranking menggunakan model cross-encoder&#13;
ms-marco-MiniLM-L-6-v2, serta menghasilkan jawaban melalui model Gemini2.5&#13;
Flash.&#13;
Hasil&#13;
evaluasi&#13;
terhadap&#13;
42&#13;
kueri&#13;
gold&#13;
set&#13;
dari&#13;
Hukumonline&#13;
menunjukkan&#13;
&#13;
nilai&#13;
&#13;
Recall@k sebesar 0,619 dan Mean Reciprocal Rank (MRR) 0,351 yang&#13;
mengindikasikan efektivitas penempatan dokumen relevan pada peringkat awal,&#13;
serta skor faithfulness 0,478 yang mencerminkan tantangan penalaran pada kueri&#13;
alami. Kontribusi penelitian berupa rancangan pipeline RAG yang robust ini dapat&#13;
dimanfaatkan oleh masyarakat umum dan praktisi sebagai alat bantu verifikasi&#13;
hukum yang akurat untuk meminimalisir kesalahan interpretasi.</mods:abstract><mods:classification authority="lcc">000 Ilmu komputer, informasi dan pekerjaan umum</mods:classification><mods:classification authority="lcc">004 Pemrosesan data dan ilmu komputer</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2026-01-22</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>Universitas AMIKOM Yogyakarta;Fakultas Ilmu Komputer</mods:publisher></mods:originInfo><mods:genre>Thesis</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_32198"><mets:rightsMD ID="rights_eprint_32198_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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