Sistem Rekomendasi Produk Skincare Pria Menggunakan Metode Content Based Filtering Dengan Algoritma Knn
Abstract
Penelitian ini bertujuan untuk mengembangkan sistem rekomendasi produk skincare pria berbasis web dengan menerapkan metode Content-Based Filtering (CBF) yang dikombinasikan dengan algoritma K-Nearest Neighbors (KNN). Sistem ini dirancang untuk membantu pengguna memperoleh rekomendasi produk skincare yang sesuai dengan jenis kulit, preferensi, serta kebutuhan individu secara akurat dan personal. Proses pengembangan melibatkan pembobotan fitur produk menggunakan Term Frequency–Inverse Document Frequency (TF-IDF) serta pengukuran kemiripan preferensi pengguna dengan algoritma KNN. Implementasi sistem dilakukan menggunakan framework Flask dan basis data MySQL. Hasil pengujian menggunakan metode Black Box dan White Box menunjukkan bahwa integrasi antara CBF dan KNN menghasilkan rekomendasi yang lebih relevan dan efisien dibandingkan metode tunggal. Hasil penelitian ini diharapkan berkontribusi dalam pengembangan sistem rekomendasi berbasis algoritma hybrid serta membantu pengguna dalam memilih produk skincare pria yang sesuai.
Kata kunci: Sistem rekomendasi, Skincare pria, Content-Based Filtering, K-Nearest Neighbors, TF-IDF.
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