Rainfall Characteristic and Prediction in Central Maluku Using Markov Chain - Tentua, Gilldo; Waas, Valencia; Kais, Siti Djasmin; Potimau, Grace A.; Soulisa, Jihan A. S.; Wattimanela, Henry Junus (Jurusan Matematika FMIPA Universitas Pattimura, 2025)
This study analyzes rainfall characteristics in Central Maluku Regency using Markov Chain methodology to model stochastic rainfall patterns. Monthly rainfall data from 2015-2024 were categorized into dry (<100 mm), normal (100-200 mm), and wet (>200 mm) conditions and processed using Microsoft Excel and R software. Results show rainfall conditions stabilize with long-term probabilities of 44.25% for wet, 32.89% for normal, and 22.87% for dry conditions. The system reaches steady state in 19 months, with 2025 predictions following this distribution. Findings support agricultural planning, disaster mitigation, and sustainable resource management in this climate-vulnerable archipelagic region.