Difana Meilani

Currency Exchange Rate Forecasting Using Artificial Neural Networks Backpropagation Method

Since 1997, the rupiah currency has a tendency to change at any time since the economic crisis that hit Indonesia. One of the most widely traded currencies in the international exchange market is the U.S. dollar. This paper forecasts the exchange rate by using back propagation neural networks. Variables that affecting currency exchange rates is inflation, gross national product and interest rates. After performing data processing with the help of software VB.net forecasting results and forecasting program, it is displayed online by using PHP to construct the webpage.

Fuzzy Multi-objective Supplier Selection Problem: Possibilistic Programming Approach

In this paper, a multi-objective mathematical model is developed in fuzzy environment in which the vagueness in aspiration level of objectives and data imprecision regarding the selection criteria and related constraints are considered simultaneously as a source of fuzziness. In the model, such data imprecision is presented based on the estimation of its possibility distribution to better capture the uncertainty. Finally, a fuzzy solution methodology is constructed by the aid of weighted additive aggregation function to derive optimal solution. As preliminary investigation, we report that the proposed model is more flexible and convenient than the previous models whose imprecise parameters are treated as a given single estimated value.