Peramalan Data Runtun Waktu Menggunakan Metode Wavelet-VAR
DOI:
https://doi.org/10.26555/konvergensi.v7i2.19603Keywords:
Trnsformasi Wavelet, Vektor Autoregressive, DenoisingAbstract
Peramalan adalah kegiatan meramalkan kejadian yang akan datang berdasarkan data dari kejadian sebelumnya. Data yang digunakan dalam penelitian ini adalah data deret waktu. Penelitian ini mengembangkan metode peramalan yang menggabungkan penggunaan wavelet dalam vector autoregressive (VAR). Wavelet digunakan sebagai alat denoising sebelum dimasukkan ke dalam persamaan regresi menggunakan vektor autoregresif. Metode ini disebut metode Wavelet-VAR. Dalam implementasinya, data deret waktu ditransformasikan menggunakan transformasi wavelet diskrit (DWT) untuk mendapatkan koefisien perkiraan dan koefisien detail. Selanjutnya noise yang terdapat pada koefisien detail dihilangkan dengan menggunakan metode thresholding tertentu. Melalui inversi transformasi wavelet diskrit (IDWT), data baru bebas noise diperoleh. Selanjutnya data bersih ini digunakan dalam peramalan dengan metode vector autoregressive. Dalam implementasinya, diterapkan data curah hujan di Kabupaten Sleman mulai Desember 2019 hingga April 2020 yang diperoleh dari situs resmi Badan Meteorologi, Klimatologi, dan Geofisika (BMKG). Untuk mengukur kualitas kualitas peramalan digunakan mean square error (MSE). Metode Wavelet-VAR menghasilkan MSE 0,354 sedangkan metode VAR menghasilkan MSE 0,838. Dalam hal ini, metode Wavelet-VAR lebih baik daripada metode VAR.References
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