PREDICTION OF RAINFALL IN DKI JAKARTA PROVINCE BASED ON THE FOURIER SERIES ESTIMATOR
(1) Department of Mathematics, Faculty of Science and Technology, Airlangga University, Indonesia
(2) Department of Mathematics, Faculty of Science and Technology, Airlangga University, Indonesia
(3) Department of Mathematics, Faculty of Science and Technology, Airlangga University, Indonesia
(4) Department of Mathematics, Faculty of Science and Technology, Airlangga University, Indonesia
(5) Department of Mathematics, Faculty of Science and Technology, Airlangga University, Indonesia
(*) Corresponding Author
Abstract
Abstract: Rainfall is the height of rainwater in a rain gauge on a flat place that does not seep and flow, where rainfall is measured in millimeters (mm). This study aims to estimate and model the rainfall for DKI Jakarta Province from January 2016 to December 2021 using the Fourier series estimation. Based on the results of the study, a model with a minimum GCV value of 21909,4, at the 7th 𝝀 43,78972. This model shows that the predictor variable can explain the diversity of response variables by 94,14%.
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Handmer, J., Honda, Y., Kundzewicz, Z. W., Arnell, N., Benito, G., Hatfield, J., et al,”Changes in Impacts of Climate Extremes: Human Systems and Ecosystems. In C.B. Field, V. Barros, T. F. Stocker, & Q. Dahe (Eds.), Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation,” Cambridge:Cambridge University Press, pp. 231–290, 2012
N. Chamidah, S. D. Febriana, R. A. Ariyanto, and R. Sahawaly , "Fourier series estimator for predicting international market price of white sugar," AIP Conference Proceedings 2329, 060035, 2021
Desvina, A. P., dan Ratnawati,”Penerapan model vector autoregressive (VAR) untuk peramalan curah hujan kota pekanbaru. Jurnal Sains, Teknologi dan Industri,” 11(2), pp. 151–159, 2014
Eubank. R, L, “Nonparametric Regression and Spline Smoothing Second Edition,” New York: Marcel Deker, 1999
Bilodeau. M, “Fourier Smootherand Additive Models, TheCanadian of Statistic,” 3, pp. 257-259, 1992
Wei, W. W. S. “Time Series Analysis, Univariate and Multivariate Methods, Second Edition,” United State of America: Pearson Education, Inc, 2006
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DOI: https://doi.org/10.26714/jsunimus.10.2.2022.34-42
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