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All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) UNP Journal of Statistics and Data Science
Tessy Octavia Mukhti
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Medicine & Pharmacology Social Sciences

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Peramalan Konsentrasi PM2.5 di Kota Medan Menggunakan Metode ARIMAX dengan Faktor Meteorologi sebagai Variabel Eksogen Fauzan Arrahman; Tessy Octavia Mukhti; Dony Permana; Fenni Kurnia Mutiya
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss4/429

Abstract

Particulate Matter 2.5 (PM2.5) is a fine particle measuring less than 2.5 micrometers which is dangerous for human health because it can penetrate the respiratory system and cause cardiovascular disorders. High PM2.5 concentrations reflect a decline in air quality, so forecasting efforts are needed to support pollution control and environmental policies. This study aims to forecast daily PM2.5 concentrations in Medan City using the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) method by considering meteorological factors as exogenous variables. The data used consist of PM2.5 concentrations and average temperature, humidity, rainfall, and wind speed data for the period from June 1, 2024 to June 10, 2025. The analysis results show that the best model is ARIMAX (4,1,0) with exogenous variables of average temperature and rainfall, where temperature has a positive effect and rainfall has a negative effect on PM2.5. This model meets the assumptions of white noise and residual normality, with a MAPE value of 20.635%, indicating a fairly good level of forecasting accuracy. The forecasting results show PM2.5 concentrations in the range of 19–26 µg/m³ with a downward trend at the end of June 2025, indicating improved air quality in Medan City. Thus, the ARIMAX method with meteorological factors is considered effective in modeling and forecasting PM2.5 dynamics in urban areas.
Co-Authors Adinda Putri Aditya, Muhammad Fadhil Aditya Admi Salma Afifah Nabilah AL Rezki Ivansyah Andini Diva Luthfiyah Anggara, Rudi Annisa Ramadhani Ardhi, Sonia Arssita Nur Muharromah Atus Amadi Putra Azizah Apriyerni Berliana Nofriadi Bimbim Oktaviandi Bunga Miftahul Barokah Bunga Nafandra defal aditya defran Dewi Febiyanti Dina Fitria Dina Fitria, Dina Dodi Vionanda Dony Permana Ervi Dayana Putri Fadhilah Fitri fajriyanti nur, Putri Fauzan Arrahman Fenni Kurnia Mutiya Fikra, Hidayatul Fitri, Fadhilah Fitri, Fitri Hayati Hariati Ainun Nisa Herlena Purnama Sari Ihsan Dermawan Inna Auliya kartika, anice Martia Rosada Nikma Hasanah Nonong Amalita Novi, Yoli Marda Nurul Mulya Syahwa Olga Afrilly Putri Putri Yeni, Dicha Rahmatul Annisa Rahmika Alya Rivani, Putri RR. Ella Evrita Hestiandari Sari Agustin Sepniza Nasywa Siregar, Fauzan Al-Hamdani Siti Nurhaliza Sri Wahyuni Syafriandi Syafriandi Wafiq Alya Aufa Yenni Kurniawati Yoli Marda Novi Yonggi, Yonggi Septa Pramadia Zamahsary Martha Zilrahmi, Zilrahmi