IDENTIFIKASI POLA CURAH HUJAN DI SUMATERA UTARA DENGAN METODE FAST FOURIER TRANSFORM (FFT) MENGGUNAKAN MEACHINE LEARNING SEBAGAI KONTRIBUSI UNTUK KASUS MATA KULIAH FISIKA KOMPUTASI

RAHMA, ZAHRA AULIA and Ariska, Melly (2024) IDENTIFIKASI POLA CURAH HUJAN DI SUMATERA UTARA DENGAN METODE FAST FOURIER TRANSFORM (FFT) MENGGUNAKAN MEACHINE LEARNING SEBAGAI KONTRIBUSI UNTUK KASUS MATA KULIAH FISIKA KOMPUTASI. Undergraduate thesis, Sriwijaya University.

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Abstract

The rainfall data studied aims to determine recurring patterns within a certain time period related to rainfall in an area. Fast Fourier Transform (FFT) is a form of transformation that is commonly used to change signal representation from the time domain to the frequency domain. This research uses the FFT method with the help of machine learning to identify rainfall patterns in the North Sumatra region at three different BMKG stations for 40 years from 1981-2020. The results show that the North Sumatra region is included in the Equatorial rainfall pattern because the rainfall pattern that is formed is the two peaks of the rainy season, namely in the 6th month and 12th month and the results of the correlation between rainfall and IOD and ENSO show that at the Kualanamu and ENSO meteorological stations The North Sumatra climatological station is more influenced by the IOD phenomenon, while the Tobing Meteorological Station is more influenced by the ENSO phenomenon.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Rainfall, pattern prediction, Fast Fourier Transformation (FFT), North Sumatra
Subjects:	Q Science > QC Physics > QC980-999 Climatology and weather
Divisions:	06-Faculty of Education and Educational Science > 84203-Physics Education (S1)
Depositing User:	Zahra Aulia Rahma
Date Deposited:	23 Jan 2024 04:21
Last Modified:	23 Jan 2024 04:21
URI:	http://repository.unsri.ac.id/id/eprint/139367

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