Spatial Pattern Analysis of Schmidt–Ferguson Climate Classification in Gorontalo Province Based on Rainfall Data - Gifari S Pratama; Ahmad Syamsu Rijal S; Talha Dangkua; Dewa Oka Suparwata (Jurnal Penelitian Pendidikan IPA, 2026)
Climate change has altered rainfall patterns in Indonesia; however, spatially detailed climate classification in Gorontalo Province remains limited. This study aims to identify climate patterns using the Schmidt–Ferguson method combined with spatial analysis. The novelty lies in integrating data consistency testing, quantitative Q index analysis, and GIS-based interpolation to produce spatial climate zoning. This study uses monthly rainfall data from 41 consistent observation stations (out of 48 stations) during 2015–2024, obtained from BWS Sulawesi II and BMKG. Data consistency was tested using the Double Mass Curve method, followed by calculation of the Q index and spatial interpolation using the Inverse Distance Weighting (IDW) method. Results show that rainfall data are highly consistent (R² ≈ 1). The Q index ranges from 7.6 to 119, indicating diverse climate types: very wet (A), wet (B), moderately wet (C), moderate (D), and slightly dry (E). Spatially, wet climates dominate mountainous areas, while relatively drier conditions occur in coastal regions. These findings are applicable for crop calendar planning, irrigation management, and disaster mitigation such as flood-prone and drought-prone zoning. However, the study is limited by uneven station distribution and a 10-year observation period. In conclusion, Gorontalo Province exhibits high spatial variability of climate influenced by topography and geographic location.