Time Series Analysis of UV Radiation and Temperature Using Seasonal ARIMA - Rahmatul Fauzi; Tasyaul Husna; Izzul Akrami; Novi Reandy Sasmita (Infolitika Journal of Data Science, 2026)
High exposure to ultraviolet (UV) radiation in Banda Aceh poses significant risks to public health and the environment. Daily forecasts of UVA, UVB, and maximum temperature are important for climate planning. But current models often overlook daily changes in tropical regions or fail to incorporate them into their forecasts. This study develops a climatologically informed SARIMA framework incorporating a semiannual seasonal structure (s = 180) to model ultraviolet radiation and temperature dynamics in an equatorial tropical region. The variables used were UVA (W/m²), UVB (W/m²), and maximum temperature (°C) in Banda Aceh during the period December 2018-July 2024. The SARIMA method was applied after data pre-processing, such as Box-Cox transformation that stabilizes the variance (λ ≈ 1) and seasonal differencing (s = 180 days) to overcome non-stationarity. Model identification using ACF/PACF plots, with diagnostic tests (Ljung-Box white noise test, Shapiro-Wilk normality test) and accuracy metrics (MAPE, MASE, BIC, and AIC) for optimization. SARIMA(1,0,2)(1,1,0)¹⁸⁰ was selected as the optimal model for all variables. The selected SARIMA models yielded MAPE values of 18.93% (UVA), 0.48% (UVB), and 13.03% (temperature), indicating that the selected SARIMA specifications were able to capture the dominant temporal patterns observed in the analyzed dataset. The peak values for March-April 2025 were predicted to be 17.69 W/m² (UVA), 0.69 W/m² (UVB), and 31.85°C.