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Andriani, Putu Eka
Universitas Airlangga
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

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Prediction and Analysis of The Number of ARI Cases based on PM2.5 Concentration with Co-Kriging Approach Chamidah, Nur; Andriani, Putu Eka; Fitri, Marfa Audilla; Fajrina, Sofia Andika Nur; Suryono, Alda Fuadiyah; Alexandra, Victoria Anggia
Inferensi Vol 8, No 1 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i1.20512

Abstract

Air quality significantly impacts global environmental health, influencing both human well-being and climate change. According to the World Health Organization (WHO), air pollution is one of the most substantial environmental threats to human health, with Indonesia experiencing particularly severe air quality issues. The World Air Quality Report ranks Indonesia 14th globally and 1st in Southeast Asia for poor air quality, with a notable increase in PM2.5 concentrations to 37.1 µg/m³ in 2023. Major sources of pollution include coal-fired power plants, motor vehicles, forest fires, and agricultural activities. In urban areas like Surabaya, PM2.5 levels have risen, contributing to high incidences of Acute Respiratory Infections (ARI). Spatial analysis reveals a correlation between PM2.5 levels and ARI cases, with spatial regression and co-kriging methods offering accurate estimation models. This study utilizes co-kriging, incorporating PM2.5 data from nine districts in Surabaya, to estimate ARI cases. The Exponential semivariogram model provided the most accurate predictions, with a MAPE value of 5.11%. The highest estimated ARI cases were in the Kenjeran district, highlighting the need for targeted interventions. Future research should expand observation points and consider additional influencing factors such as weather, population density, and socioeconomic conditions to enhance prediction accuracy and support effective public health strategies.
Co-Authors Alexandra, Victoria Anggia Fajrina, Sofia Andika Nur Fitri, Marfa Audilla Nur Chamidah Suryono, Alda Fuadiyah