The objective of the study was to forecast value oil and gas exports in Indonesia using ARIMA Box-Jenkins. With this prediction, it is hoped that can be a for future policy making. This export data obtained from Indonesian Central Bureau Statistics (BPS) website, raw January 2010 March 2022. predicted method with help R software. stages analysis include: stationary test, build model indication,...

In this paper an ANN model is developed to forecast the monthly inflation of Bangladesh as a function of its own previous value. The model selects a feed-forward backpropagation ANN with two inputs, one hidden layer with five hidden neurons and one output as the optimum network. The model is tested with actual time series data of inflation in case of Bangladesh and forecast evaluation criteria....

This paper proposes a technique to implement wavelet analysis (WA) for improving a forecasting accuracy of the autoregressive integrated moving average model (ARIMA) in nonlinear time-series. With the assumption of the linear correlation, and conventional seasonality adjustment methods used in ARIMA (that is, differencing, X11, and X12), the model might fail to capture any nonlinear pattern. Ra...

This study examines the forecasting performance of Adaptive Neuro Fuzzy Inference System(ANFIS) compared in comparison to statistical autoregressive integrated moving average (ARIMA) and the artificial neural network (ANN) model in forecasting of rice yield production.. To assess the effectiveness of these models, we used 9 years of time series records for rice yield data in Malaysia from 1995 ...

abstract the aim of this study was to selecting the suitable model for forecast land, production and price of sugar beet in iran. for this purpose, models applied to forecast are arima, single and double exponential smoothing, harmonic, artificial neural network and arch for period 1993-2008. results of durbin-watson tests, land, production and price of sugar beet series were found non stochast...

on one hand, oil is the greatest energy resource in the world and, on the other hand, because of the role of oil revenue in the economic of oil producer countries, such as iran,it is vital for these countries. so it is necessary to recognize different affective parameters on oil market for these countries. in this research, we try to forecast oil price as an important variable in world wide oil...

Abstract Background: Decision makers use the process of determining best course action by processing, analysing & interpreting data to gain insights, known as Business Intelligence. Some decision support systems sales figures predict future expansion, but few consider effect customer data. Objectives: The main objective this study is build a model that will give forecast based on fine-tuned...