SEGMENTASI PELANGGAN BERBASIS MEDIA SOSIAL DI LINGKUNGAN UKSW MENGGUNAKAN K‑MEANS UNTUK PERSONALISASI PENAWARAN PRODUK FASHION DAN KECANTIKAN

Cantika Tallo

doi:10.31539/sxzh8885

Authors

Cantika Tallo Universitas Kristen Satya Wacana

DOI:

https://doi.org/10.31539/sxzh8885

Abstract

Penelitian ini bertujuan untuk melakukan segmentasi pelanggan berdasarkan data interaksi media sosial pada industri fashion dan kecantikan menggunakan algoritma K-Means. Data yang digunakan meliputi indikator engagement seperti likes, comments, shares, saves, hashtag, mention, dan panjang caption. Tahapan penelitian meliputi preprocessing data, penentuan jumlah klaster menggunakan metode Elbow dan Silhouette, serta proses clustering. Hasil penelitian menunjukkan bahwa jumlah klaster optimal adalah dua, yaitu kelompok dengan tingkat keterlibatan tinggi dan rendah. Klaster dengan engagement tinggi menunjukkan interaksi yang lebih aktif terhadap konten, sedangkan klaster dengan engagement rendah menunjukkan respons yang lebih pasif. Hasil segmentasi ini dapat digunakan sebagai dasar dalam menyusun strategi pemasaran yang lebih personal dan tepat sasaran. Penelitian ini membuktikan bahwa data mining berbasis media sosial efektif untuk memahami perilaku konsumen.

Kata Kunci: Clustering, Data Mining, K-Means, Media Sosial, Segmentasi Pelanggan

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