Optimasi Fuzzy Time Series Untuk Prediksi Jumlah Produksi SAGA Leather Fashion Menggunakan Metode Algoritme Genetika - Aditya Chandra Nurhakim; Budi Darma Setiawan; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Leather wallets are an item that has a lot of interest nowadays, but because the process of makingproducts handmade and the price of raw materials is increasingly expensive, so making wallets andother leather-based goods has a higher price value, which makes the producers have decreasedorders. Therefore, an effort is needed to optimize the remaining raw materials used by predicting thenumber of items to be produced in the following month. The prediction method used to solve theproblem in predicting the amount of production is fuzzy time series, which is then optimized using thegenetic algorithm method. From the results of these studies, it is expected that the predicted resultscan help producers in optimize the remaining raw materials in the production process. In this study,the best individual from genetic algorithm on wallet products produce a RMSE (Root Mean SquareError) value of 5.24611658 with an accuracy rate of 96.44%, where the RMSE value is smaller thanthe test without optimization which results in a RMSE value of 7.20507068 with an accuracy of95.06%.