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ITS » Research Report » Statistika
Posted by dwi at 18/03/2008 15:50:54  •  18271 Views


PEMODELAN TIME SERIES PADA KECEPATAN ANGIN DL KOTA SURABAYA DAN SUMENEP DENGAN METODE VECTOR AUTOREGRESSIVE VAR

Author :
Irhamah, Dwi Endah Kusrini, Eling Anindita 




ABSTRAK

Sebagai salah satu parameter meteorologi yang penting kecepatan angin bermanfaat untuk mendeteksi polusi udara terutama di daerah perkotaan take-off dan landing pesawat terbang ramalan cuaca metalurgi pengairan tanaman studi pergeseran tanah kecepatan aliran air pertambangan pabrikasi industri dan sistem peringatan dini untuk bencana alami. Oleh karena itu studi mengenai fenomena kecepatan angin sangatlah diperlukan terutama untuk mengetahui model peramalannya. Penelitian tentang pemodelan kecepatan angin di dua yang berdekatan di Indonesia yaitu Surabaya dan Sumenep telah dilakukan tetapi masih di dalam kerangka univariate time series. Dalam penelitian ini akan disajikan penerapan metode multivariate time series yakni Vector Autoregression VAR untuk memodelkan kecepatan angin pada stasiun Juanda-Surabaya dan Sumenep-Madura sekaligus untuk mengetahui keterkaitan hubungan antar keduanya. Data yang digunakan adalah rata-rata harian kecepatan angin dalam knots selama 6 bulan September 2004 sampai Pebruari 2005. Langkah pertama analisis data adalah identifikasi yang dimulai dengan pengujian asumsi stasioneritas melalui statistika deskriptif plot fungsi autocorrelation ACF dan plot matriks fungsi autokorelasi. Hasil pengujian menunjukkan bahwa terdapat non-stasioneritas sehingga differencing dilakukan untuk mengatasi non-stasioneritas dalam mean dan transformasi akar pangkat dua untuk mengatasi non-stationeritas dalam varians. Setelah itu metode VAR diterapkan pada data yang sudah stasioner. Pemodelan VAR pada kecepatan angin di Surabaya dan Sumenep menghasilkan model yang terbaik VAR 4 dari model VAR tersebut diketahui bahwa untuk Surabaya kecepatan angin dipengaruhi oleh kecepatan angin Surabaya sendiri pada satu hari sebelumnya dua hari sebelumnya dan tiga hari sebelumnya. Sedangkan untuk Sumenep selain dipengaruhi kecepatan angin daerah Sumenep sendiri yaitu pada satu hari sebelumnya dua hari sebelumnya tiga hari sebelumnya empat hari sebelumnya dan lima hari sebelumnya juga dipengaruhi oleh kecepatan angin Surabaya pada empat hari dan lima hari sebelumnya. Kata kunci kecepatan angin time series vector autoregression


ABSTRACT

As one of important meteorology parameters wind speed is very useful to detect air pollution for the need of take off and landing of airline weather forecast metallurgy irrigating study of land friction mining manufacturing industrial and early warning system for natural disaster. Therefore the study of wind speed phenomenon is needed especially to know its forecasting model. Research about modeling wind speed in two bunch up town in Indonesia that is Surabaya and Sumenep have been conducted but still in univariate time series way. In this paper we present the use of multivariate time series method that is Vector Auto Regression VAR for modeling wind speed at Juanda-Surabaya and Sumenep-Madura and also for finding relationship between these two variables. The data used here was the daily mean of wind speed data measured in knots for 6 months September 2004 until February 2005. The first step in data analysis was identification that started with the examination of stationarity assumption based on descriptive statistics Autocorrelation Function ACF plot and Matrix ACF plot Examination results indicated that there were non-stationarity in mean and variance so that first differencing was done to overcome non-stationarity in mean and root-square transformation was done to overcome non-stationarity in variance. Afterwards VAR method was applied to the stationer data. Modeling with VAR to the wind speed data in Surabaya and Sumenep yield the best model VAR 4. Beside affected by itself at one two three four and five days before wind speed in Sumenep also affected by wind speed in Surabaya at four and five days before. While wind speed in Surabaya is only affected by itself at one two and three days before. The strong relationship between these two variables also shown by a high measure-6f correlation between them. Keywords wind speed time series vector autoregression



KeywordsVector Autoregressive (VAR) ; Kecepatan angin ; Time series
 
Subject:  Analisis multivarian
Date Create: 18/03/2008
Type: Text
Format: pdf ; 85 pages
Language: Indonesian
Identifier: ITS-Research-3100007069459
Collection ID: 3100007069459
Call Number: ITS 519.55 Irh p


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