Simulasi Prediksi Total Hujan Bulanan di Tanjungpinang (Studi Kasus Tahun 2017)
DOI:
https://doi.org/10.21009/JSA.02201Keywords:
monthly rainfall, multiple linear regression, correlationAbstract
The amount of rainfall that occurs in an area is affected by meteorological and non-meteorological factors. Meteorological factors or physical parameters such as air temperature, air pressure, air humidity, wind speed, and solar radiation time are indicated to affect the amount of rainfall. Simulation of the estimated monthly rainfall for 2017 using the 1981-2016 weather parameter data in Tanjungpinang was formulated using the multiple linear regression equation method. Validating of the correct results of the estimated amount of rainfall on the actual rainfall using Pearson Correlation to determine data deviations occurs between predictor to observation data. The data processing results show that the monthly rainfall prediction simulation will be quite good if the weather conditions in an area are in a normal condition which there is no weather and climate anomaly especially on a global, regional and local factor scale.