Prediksi Safety Stock Penjualan Produk Filter Solar Alat Berat Menggunakan Pendekatan DR-ARMA (Studi Kasus: PD. Borneo Diesel)

Andre Saputra, Andre Prasetya Willim, Jimmy Tjen

Abstract


Pengendalian persediaan pada data penjualan yang fluktuatif dan bersifat sparse menuntut metode peramalan yang adaptif dan akurat. Penelitian ini menggunakan data penjualan harian dengan tingkat sparsity sebesar 86 persen dan membandingkan tiga pendekatan prediksi, yaitu ARMA klasik, DR-ARMA, dan Gradient Boosting Regression (GBR), sebagai dasar penentuan safety stock. Hasil evaluasi menunjukkan bahwa DR-ARMA memiliki performa terbaik dengan nilai MAPE sebesar 11,91 persen, jauh lebih rendah dibandingkan ARMA klasik (1.578,17 persen) dan GBR (72,89 persen). Pada tahap perhitungan safety stock, DR-ARMA tetap unggul dengan akurasi yang konsisten di seluruh periode lead time. Temuan ini menunjukkan bahwa DR-ARMA merupakan metode yang efektif pada data bersifat fluktuatif atau sparse.

Keywords


Demand Response, Filter Solar, Data Sparse, Pengendalian Persediaan.

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DOI: https://doi.org/10.17509/ijdb.v5i4.93440

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