Penerapan Metode Fuzzy Time Series Chen Orde Tinggi Pada Peramalan Hasil Penjualan (Studi Kasus: KPRI “Serba Guna” Kecamatan Selorejo Kabupaten Blitar) - Nur Misbahul Arfiana; Evawati Alisah; Dewi Ismiarti (Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang, 2022)
The most developed forecasting method currently is the time series, which uses a quantitative approach with past data as a reference for future forecasting. Fuzzy time series is a solution that uses time series data by applying fuzzy methods in forecasting. This research using fuzzy time series is applied on data from the sale of the Republic of Indonesia Employee Cooperative (KPRI) Selorejo District, Blitar Regency in 2015-2021. This study describes the problem of forecasting the results of cooperative sales using the Fuzzy Time Series (FTS) which was developed with the High Order. The development of the method is done by improving the FTS method with mathematical rules and is applied to the stages of the process of forecasting the results of cooperative sales. Testing the results of the High Order Fuzzy Time Series forecasting using the best Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) accuracy values . The High Order Fuzzy Time Series consists of second order FTS, third order FTS and fourth order FTS. The results of the calculation of the smallest accuracy values are found in the fourth-order FTS, namely MSE of 19,333,658,980,372, MAPE of 11%, and MAE of 267,749. So it can be concluded that the fourth-order FTS is the best method in this study.