Skripsi
ANALISIS POLA CURAH HUJAN DI SULAWESI DENGAN METODE FAST FOURIER TRANSFORM (FFT) DAN EMPIRICAL ORTHOGONAL FUNCTION (EOF) MENGGUNAKAN MACHINE LEARNING
Rainfall in Indonesia is influenced by complex factors, including El Niño, La Niña, the Asian monsoon, diverse topography, and land-sea interactions, which shape varying weather patterns and rainfall intensity. This study analyzes rainfall patterns in Sulawesi Island from 1981 to 2015 using the Fast Fourier Transform (FFT) and Empirical Orthogonal Function (EOF) methods with a machine learning approach. The analysis results show that the EOF method successfully identifies three main modes of rainfall variability, with EOF Mode 1 capturing negative anomalies, while EOF 2 and EOF 3 capture both positive and negative rainfall anomalies. Meanwhile, the FFT analysis reveals monsoonal and equatorial rainfall patterns, with a 12-month annual cycle as the dominant pattern. Global factors such as ENSO and IOD also influence rainfall variability, impacting drought periods and increases in extreme rainfall.
Inventory Code | Barcode | Call Number | Location | Status |
---|---|---|---|---|
2507001268 | T167929 | T1679292025 | Central Library (Reference) | Available but not for loan - Not for Loan |
No other version available