Sistem Rekomendasi Distribusi Produk Menggunakan Metode Collaborative Filtering
Keywords:
Collaborative Filtering, Sistem Rekomendasi, Distribusi Produk, Peramalan Permintaan, Model HibridaAbstract
Penentuan jumlah distribusi produk ke tiap outlet di PT Zircon Euro Asia masih banyak bergantung pada perkiraan staf, sehingga berisiko menimbulkan overstock dan understock. Penelitian ini mengusulkan model hibrida berbobot yang menggabungkan sinyal tren toko berbasis exponential smoothing dan sinyal item-based Collaborative Filtering (CF) berbasis cosine similarity untuk merekomendasikan kuantitas distribusi per toko dan produk. Bobot hibrida dipilih dari data validasi pada grid 0 sampai 1, bukan ditetapkan berdasarkan perkiraan. Evaluasi memakai pembagian data berurutan menurut waktu dengan pembanding tren toko saja, moving average, dan CF saja. Kualitas ranking mesin CF diuji dengan leave-out testing pada 21.051 basket uji dari 10 wilayah dengan pembagian berbasis waktu dan menghasilkan Precision@5 sebesar 6,85% serta Recall@15 sebesar 38,63%, sehingga CF lebih tepat berperan sebagai sinyal pelengkap. Pada data uji, hibrida dengan bobot terbaik w2 = 0,2 menghasilkan MAE 1,82, RMSE 4,46, dan WAPE 54,02%, dibanding WAPE 55,36% (tren toko saja), 56,24% (moving average), dan 56,53% (CF saja); terhadap B1 unggul bermakna, terhadap B2 keunggulan tidak terbukti. Model diimplementasikan pada sistem web Laravel dan MySQL.
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