Open AccessIMPLEMENTASI PERAMALAN PENJUALAN IKAN LAUT UNTUK OPTIMASI PERSEDIAAN BAHAN BAKU (Studi Kasus di UD Harum Bungah Gresik)
Author(s) -
Khanifatus Sa'diyah,
Narto Narto
Publication year - 2021
Publication title -
jurnal rekayasa sistem industri
Language(s) - English
Resource type - Journals
eISSN - 2621-1262
pISSN - 2477-2089
DOI - 10.33884/jrsi.v6i2.2643
Subject(s) - economic shortage , demand forecasting , business , environmental science , operations management , operations research , agricultural science , fishery , mathematics , economics , marketing , linguistics , philosophy , government (linguistics) , biology
Indonesian marine waters have high marine resource resources. One of Indonesia's seafood commodities is fish. With proper management and utilization, marine products become one of the promising business opportunities for the community, so that fisheries become one of the supporting sectors of national economic development. UD Harum is one of the businesses engaged in the fisheries sector as a supplier of marine fish raw material needs to meet the needs of the manufacturing industry. To optimize production planning to meet industry demand, forecasting of sea fish sales data forecasting in the previous period is needed to anticipate a shortage of raw materials. The purpose of this forecasting is to implement forecasting using the Single Moving Average (SMA), Weighted Moving Average (WMA) and Centered Moving Average (CMA) methods in forecasting sea fish sales at UD Harum and to find out the best forecasting results to increase sea fish sales at UD Harum. Forecasting results show forecasting using the Single Moving Average (3-monthly) and (5-monthly) methods respectively 8107.67 kg and 8399.4 kg. For the Weighted Moving Average (3-monthly) and (5-monthly) methods, the results of forecasting are 7268,963 kg and 7443,452, respectively. As for the Centered Moving Average (3-monthly) method with forecast results of 8107.67 kg. The forecasting method chosen to optimize sales is the Centered Moving Average method with a forecast value of 8107.67 kg and has the smallest forecasting error compared to other forecasting methods with a MAPE value of 0.30875 and MPE of -0.1720.