<mets:mets OBJID="eprint_32138" 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="2026-07-21T07:09:37Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>EPrints Universitas Amikom Yogyakarta</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_32138_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>PENERAPAN MODEL RFM DAN CLUSTERISASI UNTUK&#13;
 SEGMENTASI PELANGGAN DI TOKO LEXON BEAUTY</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">Alif Nursetyo</mods:namePart><mods:namePart type="family">Vimanto</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>Persaingan yang ketat pada industri kecantikan menuntut Toko Lexon&#13;
Beauty untuk memahami perilaku pelanggan secara mendalam guna menghindari&#13;
hilangnya pangsa pasar akibat strategi pemasaran yang bersifat umum. Masalah&#13;
utama yang dihadapi adalah sulitnya mengidentifikasi karakteristik pelanggan&#13;
yang beragam, yang berdampak pada kurang efektifnya program loyalitas yang&#13;
telah berjalan dalam mempertahankan pelanggan lama. Penelitian ini bertujuan&#13;
untuk mengimplementasikan metode analisis berbasis data melalui pendekatan&#13;
Recency, Frequency, dan Monetary (RFM) yang dikombinasikan dengan&#13;
algoritma K-Means Clustering. Tahapan penelitian dimulai dari pra-pemrosesan&#13;
data transaksi, normalisasi menggunakan Z-score, hingga penentuan jumlah&#13;
klaster optimal melalui Elbow Method yang divalidasi dengan skor Silhouette&#13;
sebesar 0,36. Hasil penelitian berhasil mengelompokkan 1.167 pelanggan unik ke&#13;
dalam tiga segmen utama, yaitu Pelanggan Setia sebanyak 208 orang, Pelanggan&#13;
Potensial sebanyak 431 orang, dan Pelanggan Berisiko sebanyak 528 orang.&#13;
Temuan ini menunjukkan bahwa hampir separuh dari basis pelanggan berada pada&#13;
kategori berisiko yang memerlukan strategi reaktivasi segera. Hasil penelitian ini&#13;
dapat dimanfaatkan oleh manajemen Toko Lexon Beauty sebagai landasan untuk&#13;
merumuskan kebijakan pemasaran yang dipersonalisasi, seperti program Loyalty&#13;
Redemption Reward yang berjenjang. Penelitian lebih lanjut direkomendasikan&#13;
untuk menambahkan variabel demografi pelanggan guna menghasilkan klasifikasi&#13;
yang lebih komprehensif.</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">2026-03-02</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_32138"><mets:rightsMD ID="rights_eprint_32138_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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