INFLATION RATE ESTIMATION USING HYBRID ARIMA-ADAPTIVE NEURO FUZZY INFERENCE SYSTEM METHOD

Nur Alvi  Annisa; Rina Filia  Sari

doi:10.47709/cnahpc.v7i1.5534

Authors

Nur Alvi Annisa Department of Mathematics, Universitas Islam Negeri Sumatera Utara,Medan, Indonesia
Rina Filia Sari Department of Mathematics, Universitas Islam Negeri Sumatera Utara,Medan, Indonesia

DOI:

https://doi.org/10.47709/cnahpc.v7i1.5534

Keywords:

nflation, Forecasting, Hybrid ARIMA-Adaptive Neuro Fuzzy Inference System

Abstract

Inflation is an important issue that affects the economic stability of a country or region. Unstable inflation will have a negative impact on society, especially on commodity prices including food and energy. Inflation is classified as a time series and will usually recur over time, five years later, or ten years later. , the problem of inflation needs to be studied and analyzed using existing approaches in time series. This research focuses on the application of Hybrid ARIMA-Adaptive Neuro Fuzzy Inference System method for inflation estimation, which is expected to provide a more accurate picture of the price fluctuations of basic needs in North Sumatra. Overall, the results show that the ability of the Hybrid ARIMA-Adaptive Neuro Fuzzy Inference System method in estimating inflation values is quite good with the results tending to be stable and not experiencing many sharp fluctuations. The inflation value is in the range of around -2.69 to -2.73 throughout the predicted period. However, a continuous negative number indicates a price decline or economic pressure, so further analysis or development is needed to understand the cause. The estimation results may help to maintain stability or make desired changes in the future.

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https://sumut.bps.go.id/subject/3/inflasi.html