CD Skripsi

Korelasi Pm10 Terhadap Parameter Cuaca Menggunakan Model Regresi Melalui Pendekatan Deret Fourier

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Air pollution, especially PM10 in Pekanbaru City is a familiar thing. The
large population over time causes an increase in pollution that can cause diseases in
humans. Along with the development of technology, research on the relationship
between PM10 and weather parameters using a Fourier series regression approach has
been conducted. In this approach Matlab-based Fast Fourier Transform algorithm that
converts signals in the time domain to frequency signal was utilized. This study aims
to determine the PM10 cycle (frequency and period), pattern as a function of month.
The relationship of PM10 to weather parameters was determined using Fourier series
regression approach for the first 2 and 8 terms. The results show that the frequency of
monthly PM10 cycles in Pekanbaru City from 2014 to 2018 using the FFT algorithm
method, for the three selected frequencies, namely 0.0169, 0.0508 and 0.0847
cycles/month, correspond to the period of 59.00, 19,67 and 11.80 months/cycle,
respectively. PM10 connection with weather parameters such as rainfall, humidity and
temperature is periodic, so this research can use Fourier series. The 8-term Fourier
series regression is much better than that for 2-term Fourier series regression.
Keywords : PM10, signal, Fast Fourier Transform (FFT)

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

03 01.122 (0015)

Penerbit

Pekanbaru : Universitas Riau – FMIPA – FISIKA., 2022

Deskripsi Fisik

xvii, 57 hlm.: ill.: 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

03 01.122 (0015)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

FISIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

ELFITRA

Versi lain/terkait

Lampiran Berkas

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