Penerapan Metode Filter Kalman Dalam Perbaikan Hasil Prediksi Cuaca Dengan Metode ARIMA
Submission Date: 2014-08-20 12:43:13
Accepted Date: 2014-09-14 00:00:00
Abstract
Time Series merupakan salah satu metode analisis data. Salah satu metodenya adalah ARIMA Box-jenkins yang nantinya digunakan untuk meramalkan data selanjutnya. Penelitian ini didasarkan pada pengamatan dan sesuai hasil model peramalan analisis time series dari dua parameter meteorologi yaitu suhu udara dan kecepatan angin. Estimasi koefisien pada persamaan model akan dilakukan dengan menggunakan algoritma Filter Kalman. Setelah adanya penggunaan algorutma Filter Kalman akan dilakukan suatu pendekatan yang didasarkan pada koreksi linear dari bias prakiraan dalam penggunaan Filter Kalman. Selanjutnya akan lebih difokuskan pada studi parameter meteorologi satu waktu dimana diberikan sebagai direct output dari model pada waktu yang mengacu pada salah satu parameter (suhu udara atau kecepatan angin) serta sebagai bias dari prakiraan. Estimasi ini memungkinkan dalam bentuk linier pada polinomial dengan . Simulasi ini menggunakan software minitab16, matlab R2010a, dan microsoft excel. Hasil simulasi berupa grafik hasil estimasi state dalam real, ARIMA dengan minitab, dan Filter Kalman.
Keywords
ARIMA Box-Jenkins; Filter Kalman
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