Analisis Prediksi Curah Hujan Bulanan Wilayah Kota Sorong Menggunakan Metode Multiple Regression - Yusuf, Muhammad; Setyanto, Arief; Aryasa, Komang (J-SAKTI (Jurnal Sains Komputer dan Informatika), 2022)
Currently, climate change in Indonesia, which is a tropical region, is always uncertain and makes it difficult to predict weather conditions. Weather conditions can be influenced by temperature, air pressure, wind speed, humidity and rainfall. Rainfall is a climate parameter that has a high level of diversity due to climate anomalies. There are several factors that influence the characteristics of the diversity of rainfall, namely geographical, orographic, topographical, orientation and structure of the islands. These factors cause the distribution pattern of rainfall to be uneven between one area and another. For that we need a method that can solve the problem of predicting rainfall both daily, monthly and yearly. Prediction of rainfall with a statistical approach can be done through the Multiple Linear Regression method. Where in this study, rainfall is the dependent variable, while temperature and humidity are independent variables. The results obtained from the WEKA Application with a total of 60 data from 2017 to 2021, the correlation coefficient value is 0.8175, and from the evaluation results using Linear Regression, the MAE error rate is 78.8695 and the RMSE is 95.1982. It can be concluded that the effect of temperature and air on the occurrence of rainfall is 81.75%