Prediksi Tingkat Inflasi Di Indonesia Menggunakan Metode Average Based Fuzzy Time Series - Nurul Ikrima; Agus Indra Jaya; Abdul Mahatir Najar; Hajar (JURNAL ILMIAH MATEMATIKA DAN TERAPAN, 2023)
Inflation is a very important indicator in maintaining the stability of the country's economy, so it is necessary to predict the inflation rate to determine the movement of the inflation rate in the future. To predict the inflation rate in Indonesia in 2023, this research uses the Average Based Fuzzy Time Series (FTS) method based on Python programming. This method uses the principle of fuzzy set as the basis of its calculation. The data used in this study are monthly data on inflation rates in Indonesia for the period January 2013 - December 2022 obtained from the official website of Bank Indonesia (BI). The results showed that the prediction of the inflation rate in Indonesia in 2023 was in the range of 5.23% - 5.51% with the highest inflation value occurring in April and the lowest inflation value occurring in January. The accuracy level of the Average Based FTS method is calculated using the Mean Absolute Percentage Error (MAPE) of 0.820849835% which indicates that the method can be used to predict the inflation rate. Keywords : Average Based, FTS, Inflation, Prediction, Python