Optimalisasi Produksi Roti Coklat di Loren’s Bakery dengan Pendekatan Peramalan dan Fuzzy Logic Sugeno

Abstract

Loren's Bakery is one of the food industries that produces various types and flavors of bread, one of which is chocolate bread. Chocolate bread is a superior product with high demand in the market, so optimizing its production at Loren's Bakery is very important. Loren's Bakery has difficulty in optimizing the amount of production and balancing between sales and production volume. This study aims to optimize the production of chocolate bread with a forecasting approach and Sugeno fuzzy logic. The forecasting method is used to predict market demand, while Sugeno fuzzy logic handles uncertainty in the production process. In the forecasting method, a comparison of two methods is carried out, namely the Naive Method and Moving average, while Sugeno fuzzy logic, input is divided into 2 variables, namely sales and raw materials. The fuzzy set for output is a little, optimal, a lot. The results of the study showed that the Naive Method method had good results, where the error values ​​​​of MAD, MAE, and MAPE had smaller values ​​​​than the Moving average method so that the amount of sales and inventory of chocolate bread in the next period was estimated at 305 pcs and 498 kg, while the results of fuzzy logic sugeno were 335 pcs.