Fuzzy Time Series Markov Chain dalam Meramalkan Nilai Tukar Mata Uang (Kurs) Antara Ringgit Malaysia dengan Rupiah - Poppy Mangkunegara; Yerizon Yerizon (UNIVERSITAS NEGERI PADANG, 2020)
Abstract— Currency exchange rates (exchange rates) can affect the economic stability of a country. Each country conducts international relations, one of which is Indonesia and Malaysia, namely Indonesia's export activities to Malaysia. This study aims to determine the accuracy rate of forecasting with MAPE and to determine the exchange rate (exchange rate) in the next period using the Fuzzy Time Series Markov Chain. This research is applied research with secondary data taken from the official website of Bank Indonesia. By converting the exchange rate data into linguistic values and then transferring it to a fuzzy logic group to determine the markov chain transition matrix, the forecast results can be obtained. The results of processing exchange rate data using the Fuzzy Time Series Markov Chain method obtained prediction accuracy reaching 96.78% of the actual data with a MAPE value of 3.22% and the forecast results on May 4 2020 amounting to IDR 3,468. Keywords—currency exchangerate, forecasting, markov chain fuzzy time series method.