Open AccessApplication of Fuzzy Time Series-Markov Chain Method in Forecasting Data of Exchange Rate Riyal-Rupiah
Author(s) -
Dony Permana,
Isnen Fitri
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1554/1/012005
Subject(s) - currency , markov chain , value (mathematics) , fuzzy logic , context (archaeology) , time value of money , exchange rate , econometrics , computer science , series (stratigraphy) , time series , economics , operations research , mathematics , monetary economics , finance , artificial intelligence , machine learning , geography , archaeology , paleontology , biology
Currency rates are one of the important indicators in the context of an economics country. The value of a country’s currency always increases and decreases in value against another country’s currency at any time. In this research, we make a model of dynamical currency rates data among Riyals and Rupiah. The data are obtained from the official website of Bank Indonesia. The aim research is to predict the currency rate between Riyal to Rupiah in the future time with the Markov Chain Fuzzy-Time Series method. The results of this research are data processing in the form of error value of the forecast used AFER and MEA methods. Those are 0.827% and Rp32.96 rupiahs respectively. The forecast value for the next 10 days are Rp3,779; p3,774; Rp.3,774; Rp3,779; Rp3,764; Rp3,760; Rp3,763; Rp3,797; Rp3,777 and Rp3,784.