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All Journal SEMIRATA 2015 Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Ari Pani Desvina
Jurusan Matematika Fakultas Sains dan Teknologi UIN Suska Riau
Aerospace Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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PERAMALAN PENCEMARAN UDARA OLEH PARTICULATE MATTER (PM10) DI PEKANBARU DENGAN METODE BOX-JENKINS Desvina, Ari Pani
SEMIRATA 2015 Prosiding Bidang Matematika
Publisher : SEMIRATA 2015

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (340.46 KB)

Abstract

Metode Box-Jenkins adalah salah satu metode yang digunakan untuk memodelkan data deret waktu dan bertujuan untuk meramalkan data pada waktu yang akan datang. Penelitian ini membahas tentang trend data kepekatan particulate matter (PM10), dan menemukan model terbaik untuk data kepekatan particulate matter (PM10) tersebut, serta menentukan hasil peramalan pencemaran udara oleh particulate matter (PM10) di Kota Pekanbaru pada waktu yang akan datang. Data pengamatan yang digunakan adalah data rata-rata kepekatan particulate matter (PM10) secara harian mulai dari 01 Desember 2014 sampai 10 Februari 2015. Hasil analisis pada penelitian ini mendapatkan model yang sesuai untuk data particulate matter (PM10) yaitu model ARIMA(1,1,1), model ini dapat digunakan untuk analisis peramalan. Hasil peramalan menunjukkan terjadinya peningkatan kepekatan particulate matter (PM10) dari waktu sebelumnya. Sehingga tahap kualitas udara di Kota Pekanbaru untuk waktu yang akan datang dalam tahap waspada dan terjadi peningkatan pencemaran udara.   Katakunci: ARIMA, Box-Jenkins, Particulate Matter (PM10)
A Rainfall Model Comparison by Using Stochastic Neyman-Scott Rectangular Pulse (NSRP) and Bartlett-Lewis Rectangular Pulse (BLRP) Yendra, Rado; Rahmadeni, Rahmadeni; Desvina, Ari Pani
Journal of Ocean, Mechanical and Aerospace -science and engineering- Vol 53 No 1 (2018): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Publisher : International Society of Ocean, Mechanical and Aerospace -scientists and engineers- (ISOMAse)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (181.455 KB) | DOI: 10.36842/jomase.v53i1.48

Abstract

Lately, a climatic change has affected the uncertain occurrence of the rain process that implicates several difficulties in estimating flood disaster. The matter will certainly give the big problem to urban areas. Two stochastic-rain models which use the hourly rainfall data, Neyman-Scott Rectangular Pulse (NSRP) and Bartlett-Lewis Rectangular Pulse (BLRP), are a better way to identify the pattern of the rain events. Five rain characteristics represented by NSRP model’s parameter and six characteristics represented by BLRP model’s parameter will be used in identifying the rain pattern which is represented by the some rain statistics such as the probability and average of the hourly and daily rainfall. Two statistical rain models will predict the statistical value. This research using the data on 39-year rainfall per hour (1970-2008) from Alorsetar rain station has showed. It has been proved that some statistic models such as the statistical values which are generated by both models are very similar to those of observation statistics or statistics values which are generated from data.
Co-Authors Rahmadeni Rahmadeni Yendra, Rado