FORECASTING
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Prediction of Euro 50 Using Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA)
Abstract. Modeling time series is often associated with the process forecasts certain characteristics in the next period. One of the methods forecasts that developed nowadays is using artificial neural network or more popularly known as a neural network. Use neural network in forecasts time series can be a good solution,Read More
APPLICATION OF NON PARAMETRIC BASIS SPLINE (B-SPLINE) IN TEMPERATURE FORECASTING
APPLICATION OF NON PARAMETRIC BASIS SPLINE (B-SPLINE) IN TEMPERATURE FORECASTING Rezzy Eko Caraka1*, Alvita Rachma Devi1 1Department of Statistics, Diponegoro University,Indonesia *corresponding author: rezzyekocaraka@gmail.com ABSTRACT “Weather is important but hard to predict”—lay people and scientists alike will agree. The complexity of system limits the knowledge about it and thereforeRead More
THE SHIFT INVARIANT DISCRETE WAVELET TRANSFORM (SIDWT) WITH INFLATION TIME SERIES APPLICATION
Abstract Analysis of time series used in many areas, one of which is in the field economy. In this research using time series on inflation using Shift Invariant Discrete Wavelet Transform (SIDWT).Time series decomposition using transformation wavelet namely SIDWT with Haar filter and D4. Results of the transformation, coefficient ofRead More
PREDICTION OF CRUDE OIL PRICES USING SUPPORT VECTOR REGRESSION (SVR) WITH GRID SEARCH –CROSS VALIDATION ALGORITHM
Abstract The aim of this research is forecasting crude oil prices using Support Vector Regression (SVR). Algorithm to determine the optimal parameters in the model using the SVR is a grid search algorithm. This algorithm divides the range of parameters to be optimized into the grid and across all pointsRead More
TIME SERIES ANALYSIS USING COPULA GAUSS AND AR(1)-N.GARCH(1,1)
Abstract In this case, the Gauss Copula is used to connect the data that correlates with the time and with other data sets. Most often, practitioners rely only on the linear correlation to describe the degree of dependence between two or more variables; an approach that can lead to quiteRead More
PEMODELAN GENERAL REGRESSION NEURAL NETWORK (GRNN) PADA DATA RETURN INDEKS HARGA SAHAM EURO 50
ABSTRAK General Regression Neural Network (GRNN) merupakan salah satu model jaringan radial basis yang digunakan untuk pendekatan suatu fungsi. Model GRNN termasuk model jaringan syaraf tiruan dengan solusi yang cepat, karena tidak diperlukan iterasi yang besar pada estimasi bobot-bobotnya. Model ini memiliki arsitektur jaringan yang baku, dimana jumlah unit padaRead More
PREDIKSI PRODUKSI GAS BUMI DENGAN GENERAL REGRESSION NEURAL NETWORK (GRNN)
Abstrak Gas bumi sebagai salah satu sumber energi memiliki peranan yang sangat penting bagi pertumbuhan pembangunan nasional. Selama dekade terakhir, peranan gas bumi mulai menggeser peranan BBM sebagai sumber energi karena selain lebih murah juga ramah lingkungan. Pemanfaatan gas bumi di Indonesia meliputi sektor pembangkit listrik 52%, sektor industri pupukRead More
PEMODELAN GENERAL REGRESSION NEURAL NETWORK (GRNN) DENGAN PEUBAH INPUT DATA RETURN UNTUK PERAMALAN INDEKS HANGSENG
ABSTRAK Peramalan merupakan suatu unsur yang sangat penting terutama dalam perencanaan dan pengambilan keputusan. Adanya tenggang waktu antara suatu peristiwa dengan peristiwa yang terjadi mendatang merupakan alasan utama bagi peramalan dan perencanaan. Dalam situasi tersebut peramalan merupakan alat yang penting dalam perencanaan yang efektif serta efisien. General Regression Neural NetworkRead More