Implementasi Algoritme Average Time Based Fuzzy Time Series Untuk Peramalan Tingkat Inflasi Berdasarkan Kelompok Pengeluaran - Mohammad Angga Prasetya Askin; Imam Cholissodin; Sigit Adinugroho (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Inflation is a condition in which the sale price of goods or services experienced a general increase or decrease in economic activity. This affects the people of the country so that the effect is enormous. But in determining the rate of inflation is still experiencing difficulties in predicting inflation. Therefore, this study aims to determine / predict the rate of inflation by expenditure category by the Average Time Based Fuzzy Time Series method. This study uses scenarios based on consecutive monthly data, consecutive years, and the mean divisor of the difference. Inflation expense category data obtained from Indonesia Central Bureau of Statistics (BPS) and predicted results obtained is the average value of RMSE 0.486 in data month 15, the average value of RMSE 0.335 in the data year 3, and the last average RMSE 0.314 in the value of divisor 1.9 for consecutive month data categories and the mean RMSE 0.336 in the divisor value 2 for the consecutive year data categories.