Analisis Sentimen Terhadap Produk Kecantikan Emina Daily Matte Loose Powder di Emina Official Shop Menggunakan Metode Support Vector Machine

Alvena Destria Wirahadi; Sri Lestanti; Abdi Pandu Kusuma

doi:10.53697/emak.v7i1.3624

Authors

Alvena Destria Wirahadi Universitas Islam Balitar
Sri Lestanti Universitas Islam Balitar
Abdi Pandu Kusuma Universitas Islam Balitar

DOI:

https://doi.org/10.53697/emak.v7i1.3624

Keywords:

Analisis Sentimen, Support Vector Machine, TF-IDF, Emina Daily Matte Loose Powder

Abstract

Pertumbuhan e-commerce meningkatkan jumlah ulasan konsumen yang dapat menjadi sumber informasi penting bagi produsen. Namun, ulasan tersebut sering ditulis dengan bahasa tidak baku sehingga sulit dianalisis secara manual. Penelitian ini bertujuan untuk mengetahui sentimen konsumen terhadap Emina Daily Matte Loose Powder di Emina Official Shop serta menilai efektivitas metode Support Vector Machine (SVM) dalam klasifikasi sentimen. Sebanyak 1.000 ulasan konsumen dikumpulkan dari Shopee dengan teknik web scraping. Data diproses melalui tahapan pembersihan teks, casefolding, penghapusan stopwords, stemming, dan tokenisasi. Representasi data dilakukan menggunakan TF-IDF, kemudian diklasifikasikan dengan SVM kernel Radial Basis Function (RBF). Hasil penelitian menunjukkan distribusi ulasan didominasi oleh sentimen positif, sedangkan model SVM menghasilkan akurasi 70%. Metode SVM dengan kernel RBF terbukti efektif dalam mengklasifikasikan sentimen produk kecantikan.

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