Electronic Theses and Dissertation

Kilang Padi Riski Perkasa merupakan perusahaan yang bergerak dalam
bidang penggilingan padi dan produksi beras. Dalam kegiatan operasionalnya
Kilang Padi Riski Perkasa masih mengalami kendala terkait perencanaan dan
pengendalian persediaan bahan baku gabah yang belum terstruktur secara
matematis. Penelitian ini bertujuan untuk merencanakan sistem persediaan bahan
baku gabah yang optimal dengan menggunakan metode Double Exponential
Smoothing (Brown) untuk peramalan permintaan dan Algoritma Wagner Within
(AWW) untuk menentukan jumlah serta waktu pemesanan yang efisien. Data yang
digunakan adalah data pembelian gabah tahun 2024, dengan analisis akurasi
peramalan menggunakan Mean Absolute Percentage Error (MAPE), Mean
Absolute Deviation (MAD), dan Mean Squared Error (MSE), serta uji verfikasi
melalui Moving Range Chart (MRC). Hasil peramalan menunjukkan bahwa
metode DES Brown memiliki tingkat akurasi yang sangat baik, dengan MAPE
sebesar 5,228%, MAD sebesar 100.661 kg, dan MSE sebesar 18.901.630.827 kg.
Berdasarkan penerapan Algoritma Wagner Within diperoleh hasil bahwa jumlah
pemesanan optimal adalah 12 kali dalam satu tahun dengan total biaya persediaan
minimum sebesar Rp. 103.723.541, serta nilai safety stock sebesar 95.863 kg dan
reorder point (ROP) sebesar 158.120 kg. Berdasarkan hasil perhitungan kebutuhan
bahan baku dan biaya persediaan, metode Algoritma Wagner Within terbukti lebih
efisien dibandingkan sistem existing perusahaan. Total biaya persediaan existing
mencapai Rp 158.800.741.781, sedangkan metode Wagner Within hanya Rp
143.695.198.928, sehingga diperoleh penghematan sebesar Rp 15.105.542.854 atau
sekitar 10%.
Kata Kunci: Algorithma Wagner Within, Double Exponential Smoothing
(Brown), Pesediaan Bahan Baku, Safet Stock, Reorder Point

Kilang Padi Riski Perkasa is a company engaged in rice milling and rice production. In its operational activities, Kilang Padi Riski Perkasa still experiences obstacles related to planning and controlling raw material inventory of rice that has not been mathematically structured. This study aims to plan an optimal raw material inventory system for rice using the Double Exponential Smoothing (Brown) method for demand forecasting and the Wagner Within Algorithm (AWW) to determine the amount and timing of efficient orders. The data used are rice purchase data for 2024, with forecasting accuracy analysis using Mean Absolute Error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Error (MSE), as well as verification tests through Moving Range Chart (MRC). The forecasting results show that the DES Brown method has a very good level of accuracy, with a MAPE of 5.228%, a MAD of 100.661 Kg, and an MSE of 18.901.630.827 kg. Based on the application of the Wagner Within Algorithm, the optimal number of orders is 11 times per year, with a minimum total inventory cost of Rp 103.723.541, a safety stock value of 95.863 kg, and a reorder point (ROP) of 158.120 kg. Although inventory cost data for the company's previous method is not yet available, the analysis results show that the application of the AWW method is theoretically more efficient because it takes into account the relationship between ordering costs, holding costs, and demand in an integrated manner. Based on the results of the raw material requirements and inventory cost calculations, the Wagner Within Algorithm method proved to be more efficient than the company's existing system. The total existing inventory cost reached Rp 158.800.741.781, while the Wagner Within method was only Rp 143.695.198.928, resulting in savings of Rp 15.105.542.854 or approximately 10%. Keywords: Double Exponential Smoothing (Brown), Raw Material Inventory, Reorder Point Safety Stock, Wagner Within Algorithm