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ITS » Undergraduate Theses » Statistika
Posted by fandikaaqsa@its.ac.id at 20/04/2016 10:40:16  •  1022 Views


PEMODELAN KONSENTRASI PARTIKEL DEBU PM10 PADA PENCEMARAN UDARA DI KOTA SURABAYA DENGAN METODE GEOGRAPHICALLY-TEMPORALLY WEIGHTED REGRESSION

MODELING OF DUST PARTICLE CONCENTRATION PM10 ON AIR POLLUTION IN SURABAYA CITY USING GEOGRAPHICALLY-TEMPORALLY WEIGHTED REGRESSION

Author :
AISYIAH, KURNIASARI ( 1310100045 )




ABSTRAK

Konsentrasi partikel debu PM10 di Kota Surabaya menempati urutan pertama di Jawa Timur. Hal ini karena aktifitas penduduk Kota Surabaya yang tinggi menyebabkan polusi udara. Partikel debu PM10 merupakan salah satu polutan yang apabila terhisap langsung ke dalam paru-paru dan mengendap di alveoli dapat membahayakan sistem pernafasan. Dalam pemantauan kualitas udara seringkali peralatan pengukur konsentrasi partikel debu PM10 mengalami kerusakan sehingga data polutan tersebut tidak terukur atau tidak tersedia missing. Mengingat pentingnya data tersebut maka perlu dilakukan pendugaan data konsentrasi partikel debu PM10 pada lokasi yang tidak terukur. Salah satu metode yang digunakan adalah Geographically-Temporally Weighted Regression GTWRuntuk memprediksi konsentrasi partikel debu PM10 dengan menggunakan parameter meteorologi. Konsentrasi partikel debu bergantung pada lokasi dan waktu. Hasil penelitian menyimpulkan bahwa kondisi pencemaran udara di Kota Surabaya pada tahun 2010 masih dinyatakan baik artinya bernilai di bawah ambang batas. Hasil prediksi dengan metode GTWR lebih akurat daripada regresi nonspasial. GTWR dapat mengakomodasi adanya pengaruh heterogenitas spasial dan temporal pada konsentrasi partikel debu PM10.


ABSTRACT

The concentration of dust particles PM10 in Surabaya is the first ranks in East Java. This is because the activity of the population of Surabaya which causes air pollution. Dust particles PM10 is one pollutant that when inhaled directly into the lungs and settles in the alveoli may be harmful to the respiratory system. In air quality monitoring measuring equipment concentration of dust particles PM10 is often broken so the data is not measured pollutant or not available missing. Given the importance of these data it is necessary to estimate the concentration data of dust particles PM10 in locations that are not measurable. One method used is Geographically-Temporally Weighted Regression GTWRto predict the concentration of dust particles PM10 using meteorological parameters. The concentration of dust particles depends on location and time. The study concluded that the condition of the air pollution in the city of Surabaya in 2010 was declared good meaning valued below the threshold. The results of the prediction method GTWR is more accurate than the regression non-spatial. GTWR can accommodate the influence of spatial and temporal heterogeneity in the concentration of dust particles PM10.



KeywordsPartikel debu; regresi; spasial; temporal
 
Subject:  Analisis regresi
Contributor
  1. Dr. Sutikno, S.Si, M.Si
  2. Dr. Drs. I Nyoman Latra, M.S
Date Create: 20/04/2016
Type: Text
Format: PDF
Language: Indonesian
Identifier: ITS-Undergraduate-13001160008658
Collection ID: 13001160008658
Call Number: RSSt 519.536 Ais p


Source
Undergraduate Thesis of Statistics, RSSt 519.536 Ais p, 2014

Coverage
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Rights
Copyright @2016 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




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  1.  ITS-Undergraduate-41239-1310100045-abstract_id.pdf - 185 KB
  2.  ITS-Undergraduate-41239-1310100045-abstract_en.pdf - 262 KB
  3.  ITS-Undergraduate-41239-1310100045-conclusion.pdf - 355 KB




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