PERAMALAN CURAH HUJAN MENGGUNAKAN METODE ANALISIS SPEKTRAL

  • NI PUTU MIRAH SRI WAHYUNI Faculty of Mathematics and Natural Sciences, Udayana University
  • I WAYAN SUMARJAYA Faculty of Mathematics and Natural Sciences, Udayana University
  • I GUSTI AYU MADE SRINADI Faculty of Mathematics and Natural Sciences, Udayana University

Abstract

The purpose of this research is the model of forecasting rainfall using spectral analysis method. To obtain complete information on characteristics of time series data we need to examine periodicity of the data. Examining the periodicity of time series data in the frequency domain is called spectral analysis. The results of spectral analysis show that periodogram is clearly dominated by a very large peak at frequency . This frequency corresponds to period of 12 cycle per month. Based on the results of analysis of time series data rainfall is SARIMA (0,1,1)(0,1,1)12 where the model can be written as The result indicates minimum rainfall happen in January and maximum rainfall happen in August.

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Author Biographies

NI PUTU MIRAH SRI WAHYUNI, Faculty of Mathematics and Natural Sciences, Udayana University
Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
I WAYAN SUMARJAYA, Faculty of Mathematics and Natural Sciences, Udayana University
Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
I GUSTI AYU MADE SRINADI, Faculty of Mathematics and Natural Sciences, Udayana University
Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
Published
2016-11-30
How to Cite
WAHYUNI, NI PUTU MIRAH SRI; SUMARJAYA, I WAYAN; SRINADI, I GUSTI AYU MADE. PERAMALAN CURAH HUJAN MENGGUNAKAN METODE ANALISIS SPEKTRAL. E-Jurnal Matematika, [S.l.], v. 5, n. 4, p. 183-193, nov. 2016. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/25343>. Date accessed: 22 nov. 2024. doi: https://doi.org/10.24843/MTK.2016.v05.i04.p139.
Section
Articles

Keywords

Forecasting; Periodicity; SARIMA; Spectral Analysis

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