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Jakarta Composite Index Prediction Using Fuzzy Time Series Markov Chain

R.N. Rachmawati, A. Gamalita, I. Sungkawa


Predicting the future and figuring out what to do with it has always been the real business. From time series data we predict the closing price of Jakarta Composite Index (JCI) by using Fuzzy Time Series Markov Chain Model. This method includes three main concepts, the concept of Fuzzy, Time Series and Markov Chain. Fuzzy concepts are useful to classify variables, Time Series concept to observe the JCI movement during a particular period and Markov Chain concept is used in process prediction of JCI price using the transition probability matrix. The prediction result is quite accurate and can assist users in making decisions relating to the exercise of economic activity.


time series model, Markov chain, JCI

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