Prediksi Cuaca Di Provinsi Jawa Barat Menggunakan Multiple Linear Regression

Weather condition analysis is an important aspect in various sectors of life, such as agriculture, transportation, and disaster mitigation. This study aims to analyze the relationship between meteorological factors and weather conditions in the West Java Province region by using the multiple linear regression method and Microsoft Excel tools. The data used in this study included four independent variables, namely temperature (X1), humidity (X2), wind direction (X3) and wind speed (X4), as well as a dependent variable in the form of weather prediction (Y). Historical data was obtained from the Meteorology, Climatology, and Geophysics Agency (BMKG) which includes 35,363 rows of weather data at the sub-district level in West Java. The results of multiple linear regression analysis show that the weather prediction model has a determination coefficient (R2) value of 0.0481 and an adjusted R2 value of 0,0480. This indicates that independent variables only make a small contribution in explaining the variability of dependent variables. The regression equation obtained is Y = -89,0277 + 0,5766X1 + 2,4595X2 - 0,2315X3 - 0,1757X4. Despite having a relatively low R2 value, this prediction model can be used as a tool in water resource planning, disaster mitigation, and other applications that require accurate weather information. This study emphasizes the importance of weather analysis to support decision-making in various sectors, especially those related to climate and weather phenomena. Further studies are needed to improve the accuracy of weather prediction models by taking into account other influential factors.