Efektivitas Metode Least Squares dan Double Moving Average dalam Mendukung Pengambilan Keputusan Persediaan
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Abstract
Penelitian ini bertujuan membandingkan tingkat akurasi metode Least Square (LS) dan Double Moving Average (DMA) dalam meramalkan permintaan persediaan pada Toko Online Telaten Karya, sebuah usaha ritel daring bahan bangunan yang selama ini mengambil keputusan persediaan berdasarkan intuisi. Penelitian menggunakan pendekatan kuantitatif berbasis analisis deret waktu terhadap data penjualan bulanan selama dua belas bulan, dengan tingkat akurasi dievaluasi menggunakan Mean Absolute Percentage Error (MAPE). Hasil menunjukkan metode Least Square (LS) menghasilkan MAPE sebesar 15,00% (kategori akurasi baik), sedangkan metode Double Moving Average (DMA) menghasilkan MAPE sebesar 54,13% (kategori akurasi rendah), sekitar tiga setengah kali lebih tinggi. Kinerja Least Square (LS) yang lebih unggul sejalan dengan pola tren penjualan yang meningkat secara bertahap, sementara proses double smoothing pada DMA justru menimbulkan bias ke arah nilai yang lebih tinggi. Metode Least Square (LS) direkomendasikan sebagai dasar perencanaan persediaan pada UMKM tersebut.
This study compares the forecasting accuracy of the Least Squares (LS) and Double Moving Average (DMA) methods for supporting inventory demand planning at Toko Online Telaten Karya, an online retailer of building materials that previously relied on intuition-based inventory decisions. A quantitative time-series approach was applied to twelve months of monthly sales data, with forecasting accuracy evaluated using the Mean Absolute Percentage Error (MAPE). The results show that the LS method achieved a MAPE of 15.00%, classified as good accuracy, while the DMA method produced a MAPE of 54.13%, classified as poor accuracy, roughly three and a half times higher. The superior performance of LS aligns with the gradually increasing sales trend in the data, whereas the double-smoothing process in DMA introduced an upward bias. The LS method is recommended as the basis for inventory planning in this small online retail business.
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