Analisis Pertumbuhan Ekonomi dan Volatilitas dengan Menggunakan Metode Wavelet
Keywords:
Growth, Volatility, Wavelet Varians, Wavelet Correlation, WRNNAbstract
Growth Economic known as Growth is one of the most important thing in categorical or describing the condition a country. It happens as growth and volatility analysis is one of interesting topics to be researched. Although there are several method used for growth analysis and volatility, yet those isnt filled the characteristics of growth’s indicator, such stationarity, or short term and long term analysis. Wavelets are used to anticipate it, the ability to zoom in or zoom out are useful in short and long term analysis, and no stationarity assumption is one of the reason wavaelet are used lately.
In Time Series’s case wavelet present it to be two components such high frequency and low frequency, as the identification of accrelation phase of growth doesnt need to be bounded. Wavelet Varians, Wavelet Correlation, and WRNN (Wavelet Recurrent Neural Network) are a main tools in this undergraduated’s theses. Wavelet Varians is used for volatility analysis, Wavelet Correlation is used in co-movement analysis, and WRNN will predict the growth condition. Based on the the data proccesing using Matla R2015b, Indonesia is a the volatile country based on growth in short term, with the co-movement happened with Japan, Thailand, and Philippine, and also the proyectory of Indonesia’s IPI will increase.
ABSTRAK
Pertumbuhan Ekonomi merupakan hal yang paling penting dalam pengkategorian atau keadaan dalam suatu negara di dunia, menjadikan analisis pertumbuhan ekonomi dan volatilitas menjadikan topik yang selalu menarik untuk diteliti. Terdapat beberapa cara dalam analisis ekonomi, tetapi teknik tersebut masih belum dapat memenuhi karakteristik dari indikator-indikator pertumbuhan ekonomi dan volatilitas tersebut, contoh tidak stasioner, analisa jangka panjang ataupun pendek. Metode Wavelet digunakan untuk mengantisipasi hal tersebut, karena sifat wavelet yang dapat men-zoom in ataupun zoom out maka wavelet cocok untuk analisa jangka panjang ataupun pendek, dan tidak adanya asumsi yang perlu di penuhi dalam wavelet termasuk stasioneritas merupakan alasan mengapa wavelet digunakan.
Wavelet merupakan suatu metode yang sangat berguna untuk memperlajari karakteristik time – varying pada pertumbuhan ekonomi dengan detail yang sangat terperinci dan juga tidak diperlukannya asumsi stasioneritas. Dengan wavelet, kasus time series dijadikan dua komponen yaitu high frequency dan low frequency, sehingga dapat diidentifikasi fase perlambatan dan fase percepatan dari pertumbuhan ekonomi tanpa menggunakan batasan apapun. Wavelet Varians, Wavelet Korelasi dan WRNN (Wavelet Recurrent Neural Network) menjadi alat utama dalam skripsi ini. Wavelet Variansi yang akan menganalisa volatilitas, Wavelet Korelasi yang akan menganalisa co-movement, dan WRNN yang akan memproyeksi keadaan ekonominya. Berdasarkan hasil pengolah menggunakan software Matlab R2015b, Negara Indonesia merupakan negara yang bervolatilitas dalam pertumbuhan ekonomi jangka pendek, dengan co-movement terjadi dengan negara Jepang, Thailand, Philippine, dan dalam pemproyeksiannya nilai IPI Indonesia akan menaik.
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