<mets:mets OBJID="eprint_32065" 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="2026-07-21T07:09:17Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>EPrints Universitas Amikom Yogyakarta</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_32065_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>IMPLEMENTASI METODE CONTENT BASED FILTERING PADA&#13;
SISTEM REKOMENDASI FILM</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">Stefanus Dwi</mods:namePart><mods:namePart type="family">Christianto</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>Perkembangan pesat platform streaming film di era digital telah&#13;
menyebabkan lonjakan volume konten yang masif, sehingga memicu fenomena&#13;
information overload. Kondisi ini berdampak negatif pada pengalaman pengguna,&#13;
mengakibatkan kelelahan dalam pengambilan keputusan (decision fatigue) dan&#13;
inefisiensi waktu dalam menemukan tontonan yang relevan dengan preferensi&#13;
mereka. Penelitian ini bertujuan mengatasi permasalahan tersebut dengan&#13;
membangun sebuah sistem rekomendasi film menggunakan metode Content-Based&#13;
Filtering. Metodologi penyelesaian masalah dilakukan melalui beberapa tahapan&#13;
sistematis, meliputi akuisisi dataset film, pra-pemrosesan data teks, rekayasa fitur&#13;
gabungan (soup) yang mencakup genre dan sinopsis, pembobotan fitur&#13;
menggunakan Term Frequency-Inverse Document Frequency (TF-IDF), serta&#13;
perhitungan tingkat kemiripan antar dokumen menggunakan algoritma Cosine&#13;
Similarity. Sistem yang dirancang kemudian diimplementasikan ke dalam sebuah&#13;
prototipe aplikasi berbasis web fungsional. Hasil akhir penelitian menunjukkan&#13;
bahwa sistem mampu memberikan rekomendasi yang akurat dan relevan,&#13;
dibuktikan dengan evaluasi kinerja yang mencapai persentase kesamaan genre&#13;
hingga 80% dan kesamaan kru film sebesar 70% pada skenario pengujian.&#13;
Penelitian ini memberikan manfaat praktis bagi pengguna dalam mempercepat&#13;
pencarian film, serta menjadi rujukan bagi penyedia layanan hiburan untuk&#13;
meningkatkan keterlibatan pengguna melalui fitur personalisasi. Pengembangan&#13;
selanjutnya disarankan untuk mengintegrasikan metode Hybrid Filtering guna&#13;
memperkaya variasi rekomendasi.</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">2025-12-15</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_32065"><mets:rightsMD ID="rights_eprint_32065_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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