Implementasi Fuzzy Time Series Pada Prediksi Harga Daging Di Pasar Kabupaten Malang - Frans Agum Gumelar; Rekyan Regasari Mardi Putri; Indriati Indriati (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Beef is one of the staples that are always consumed by the people of Indonesia. The scarcity of local beef is one of the causes of rising prices. Stabilize the price of beef is the duty of DISPERINDAG. DISPERINDAG spreads almost in every region of Indonesia, one of them is in Malang. Its population is increasing annually so that the demand of food especially beef also increasing. Rising demand of beef also affects the rise in beef prices. So DISPERINDAG should control the increase of beef prices as action to anticipate the increasing price. Therefore, one of the efforts that can be done is to forecast increasing price of beef. So that DISPERINDAG can consider the next month price based on forecast result.The forecasting process is based on historical data. This forecasting that is used is called time series data forecasting. The relations between data are emphasized in time series forecasting. The method used for forecasting is the Fuzzy Time Series (FTS). Based on the results of the test using 21 data of meat prices in Malang Regency in 2016 and 2017, the accuracy obtained from forecasting of 57%. With the smallest error value lies in june 2017 of 16,129 and the biggest error value lies in march 2016 of 65,610,000.