Skripsi

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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407000866	T139367	T1393672024	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1393672024

Publisher

Indralaya : Prodi Pendidikan Fisika, Fakultas Keguruan dan Ilmu Pendidikan Universitas Sriwijaya., 2024

Collation

x, 40 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

551.577 07

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Curah hujan
Prodi Pendidikan Fisika

Specific Detail Info

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Statement of Responsibility

KHARISMA

Other version/related

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