Dedi Rosadi

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Since its introduction by Molodstov (Computers & Mathematics with Applications 37(4):19–31 1999), soft set theory has been widely applied in various fields of study. Soft set theory has also been combined with other theories like fuzzy sets theory, rough sets theory, and probability theory. The combination of soft sets and probability theory generates(More)
The aim of this research is to analyze ANFIS performance for prediction of financial time series data. Financial time series data is usually characterized by volatility clustering, persistence, and leptokurtic data behavior. The financial time series data are usually non-stationary and non-linear. ARIMA has a good performance to predict linear time series(More)
  • Dedi Rosadi
  • 2016 12th International Conference on Mathematics…
  • 2016
Here we introduce some new linear dependence measures, namely the generalized covariation coefficient, generalized symmetric covariation coefficient and the generalized sign symmetric covariation coefficient. These measures can be applied for random variables which fulfill a certain linearity property and have finite first moments. Some basic mathematical(More)
Foreign exchange market is one of the most complex dynamic market with high volatility, non linear and irregularity. As the globalization spread to the world, exchange rates forecasting become more important and complicated. Many external factors influence its volatility. To forecast the exchange rates, those external variables can be used and usually(More)
It has widely known that the irreversible property of Markov chain representing the multirate multiservice loss system with Trunk Reservation policy is not satisfied. In this case, the well-known product form result for state probabilities cannot be applied. To obtain the exact state probabilities, one has to solve the balance equation of Markov chain that(More)
Lung cancer is one of the deadliest types of cancer in the world. Lung cancer detection is necessary to determine the next steps in dealing with the patients. One of the methods that can be used for lung cancer detection is a classification method based on lung cancer image. Most of the models for lung cancer classification based on lung cancer image are(More)
We consider the codifference and the normalized codifference function as dependence measures for stationary processes. Based on the empirical characteristic function, we propose estimators of the codifference and the normalized codifference function.We showconsistency of the proposed estimators,where the underlyingmodel is the ARMAwith symmetric α-stable(More)
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