Kajian Metode Analisis Spektral Pada Peramalan Curah Hujan - Zega, Putri May Sari; Mardiningsih, Mardiningsih (Forum Kerjasama Pendidikan Tinggi (FKPT), 2025)
Rainfall is an important element in climate research, and its analysis requires appropriate approaches to reveal seasonal patterns and periodicity. This research aims to explore the application of the spectral analysis method in rainfall forecasting using monthly rainfall data from Serdang Bedagai Regency for 10 years (January 2014 – December 2023) totaling 120 data. The method used is harmonic analysis, a Fourier approach to extracting frequency information from time series data. This research began with data visualization, stationarity testing using the Phillips-Perron test, to spectral analysis involving calculations of Fourier coefficients and periodograms to detect dominant frequencies. The results show that the data has a periodic component with the highest frequency at 0.524, which is equivalent to a 12 month period. These results indicate the existence of seasonal patterns in rainfall data, which is relevant to support more accurate climate forecasting models. The implications of this research include the use of spectral analysis as a reliable method for identifying periodicity and building seasonal pattern-based forecasting models, which can be applied in various studies related to climate change and its mitigation.