Afsari, Fadilla
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Validitas Game Edukatif Terintegrasi Audio-Augmented Reality untuk Meningkatkan Literasi Matematis Siswa Diskalkulia Alfianita, Nova Febrian; Afsari, Fadilla; Dewi, Alvi Setya Kurnia; Rahmawati, Nabila Neva; Nafis, Tazkiyatun; Sari, Yurizka Melia
MATHEdunesa Vol. 13 No. 3 (2024): Jurnal Mathedunesa Volume 13 Nomor 3 Tahun 2024
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathedunesa.v13n3.p765-778

Abstract

Comparison of Extreme Value Logistic and Copula Approaches for Bivariate Extreme Value in Pekanbaru Afsari, Fadilla; Sofro, A'yunin
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.41081

Abstract

Global climate change has intensified extreme weather events in tropical regions, increasing heat-related risks in Pekanbaru City. This study aims to analyze the joint behavior of extreme maximum temperature and humidity using a multivariate extreme value framework. Daily data from 20142024 were processed using a seasonal block maxima approach, resulting in 24 seasonal extreme observations. The marginal distributions follow a Weibull-type Generalized Extreme Value (GEV) distribution, indicating bounded extreme values. Dependence analysis indicates a weak association, where the Joe copula converges to the independence case, while the Frank copula yields the lowest AIC value among the fitted copula models. However, the difference in AIC values is small and should be interpreted cautiously. Joint return period analysis indicates that joint exceedance of seasonal block maxima is relatively infrequent (approximately 100 years), whereas single-variable exceedances occur more frequently (approximately 5.2 years). These return period estimates are exploratory and subject to uncertainty due to the limited sample size. Overall, the results suggest a weak dependence structure between the variables, and the findings should be interpreted cautiously in the context of climate-related risk assessment.