Prediksi Penjualan Roti Menggunakan Metode Exponential Smoothing (Studi Kasus : Harum Bakery) - Reyhan Dzickrillah Laksmana; Edy Santoso; Bayu Rahayudi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Bread is a very widely known in the community and the invention in its technology was also very rapidly growing. Bread has now become part of everyday life and become staple human food. The bakery industry is constantly evolving to make bread companies do a product innovation and the right sales strategy. That is becomes a challenge for Harum Bakery to get maximum profit and suffered no losses. The predictions in this research use Exponential Smoothing method. Exponential Smoothing is a method that continuously performs forecasting improvements by taking the average value of smoothing past values from time expanding data in exponential way. In this research, prediction were performed using three Exponential Smoothing method which is, Single Exponential Smoothing, Double Exponential Smoothing, and Triple Exponential Smoothing. This method was evaluated by calculating average error rate using Mean Absolute Percentage Error (MAPE) method. The smallest MAPE for Single Exponential Smoothing method when value of Î± parameter's is 0,1 with MAPE value 27,4039%, for Double Exponential Smoothing method when value of Î± parameter's is 0,1 with MAPE value 25,124% , and for Triple Exponential Smoothing method when value of Î± parameter's is 0,1, Î² parameters is 0,1 and Î³ parameters is 0,4 with MAPE value 25,303%. So the concluded is the Double Exponential Smoothing has better accuracy than Single Exponential Smoothing and Triple Exponential Smoothing on Bread Sales Prediction Case Study of Harum Bakery.