APPLIED SOME MIXTURE 2 AND 3 DISTRIBUTION FOR DAILY EXCHANGE RATE AMERICAN DOLLAR VS INDONESIAN RUPIAH PROBABILITY MODELLING

As a world superpower, the United States has very stable exchange rate and big impact on currencies of other countries, like Indonesia. Probability modeling is therefore essential for analyzing change in rates between Indonesian rupiah (IDR) US dollar (USD). In addition to comparing distributions two parameters, this study also discusses use several mixture 2 3 component distribution probability models, such as log-normal (ML2), Gamma (MG2), Weibull (MW2), Log-Normal (ML3), (MG3), (MW3). The maximum likelihood method used parameter estimation, numerical methods Akaike Information Cretarius (AIC) Bayesian (BIC) are select best model, known Goodness Fit (GOF). Then, GOF model theoretical data evaluated. ML3 distribution-based daily USD/IDR can be modeled using MLE approach, demonstrated by results. We able reasonably forecast risks associated with exchanges future basis identified models