https://jurnal.fmipa.unm.ac.id/index.php/variansi Program Studi Statistika Fakultas MIPA UNM en-US VARIANSI: Journal of Statistics and Its application on Teaching and Research 2684-7590 https://jurnal.fmipa.unm.ac.id/index.php/variansi/article/view/402 <p>Forest and land fires are recurring ecological and socio-economic disasters in Banjar Regency, South Kalimantan Province, with complex triggers. A deep understanding of the spatial distribution of fire risk is crucial for effective mitigation efforts. This study aims to model the spatial intensity of hotspots as a proxy for forest and land fires events in Banjar Regency and produce a fire risk surface map. The data used in this study are hotspot data from the siPongi website in Banjar Regency for the period 2013–2024, along with elevation data analyzed using the Log-Gaussian Cox Process (LGCP) spatial statistical model. The analysis results show that elevation has a negative but statistically insignificant effect on hotspot intensity, where fire risk tends to be higher at lower elevations. The LGCP model proved effective in capturing the complex spatial patterns of hotspot occurrences, separating trends driven by covariates and residual spatial clustering. The resulting risk intensity map successfully identified high-risk clusters, particularly concentrated in western districts dominated by peatlands and agricultural activities.</p> Sigit Dwi Prabowo Dewi Sri Susanti Al Hujjah Asianingrum Copyright (c) 2025 VARIANSI: Journal of Statistics and Its application on Teaching and Research 2025-09-30 2025-09-30 7 2 10.35580/variansiunm402 https://jurnal.fmipa.unm.ac.id/index.php/variansi/article/view/391 <p>Kota Samarinda yang beriklim tropis memiliki curah hujan dengan variasi signifikan sepanjang tahun. Ketidakstabilan ini berpotensi menimbulkan dampak seperti banjir, gangguan pada sektor pertanian, dan kerusakan infrastruktur. Penelitian ini bertujuan untuk menganalisis serta memprediksi pola musiman terjadinya curah hujan di Kota Samarinda dengan menerapkan metode Holt Winters Exponential Smoothing model multiplikatif. Data curah hujan bulanan dianalisis untuk mengidentifikasi sifat stasioneritas pada rata-rata dan varian, dengan hasil menunjukkan bahwa data bersifat stasioner dalam rata-rata namun tidak dalam varian sehingga digunakan model Holt-Winters Exponential Smoothing Multiplikatif. Estimasi parameter model menghasilkan nilai alpha , beta , dan gamma masing-masing sebesar 1, dengan nilai MAPE sebesar 50%, yang menunjukkan tingkat akurasi sedang. Meskipun tingkat kesalahan cukup tinggi, model ini tetap mampu menggambarkan pola musiman yang berguna untuk perencanaan awal pengelolaan sumber daya air di wilayah tersebut.</p> Thesya Atarezcha Pangruruk Copyright (c) 2025 VARIANSI: Journal of Statistics and Its application on Teaching and Research 2025-09-30 2025-09-30 7 2 10.35580/variansiunm391