ANALISIS TIME SERIES PADA DATA METEOROLOGI BMKG KOTA PANGKALPINANG MENGGUNAKAN METODE MULTILAYER PERCEPTRON
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Abstract
The public has aneed for weather forecast information for a particular region because the weather inIndonesia is often changeable. Weather is the state of the atmosphere,sky, or air on Earth. Weather changes are greatly influenced by severalfactors in the surrounding area, including temperature, air temperature, air pressure,wind, and air humidity. Weather predictions can be made using various methods, one of which is the Multilayer Perceptron. Multilayer Perceptron is a development of neural networks that can be used for modeling time series data. The purpose of this research is to predict the weather using the Multilayer Perceptron method. The evaluation of the prediction results will use Mean Absolute Error (MAE) and Mean Squared Error (MSE). The results of this research are weather predictions for 2019, which are compared with actual data and produce MAE and MSE results of 0.791 and 0.821, respectively.Error (MAE) and Mean Squared Error (MSE). The results of this studyare weather predictions for 2019, which are compared with actual dataand yield MAE results of 0.791 and MSE results of 0.897 for the average temperature variableand MAE results of 2.602 and MSE results of 9.964 for the sunshine duration variable.
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