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- W57149851 abstract "Season changes conditions in Indonesia cause many disasters such as landslides, floods and whirlwinds and even hail. Extreme weather conditions that occur, it is better to remain alert to anticipate the various possibilities that occur and to reduce and minimize the impact that can harm the people. The design of weather prediction system in this research using Autoregressive Integrated Moving Average ARIMA Box Jenkins model and Kalman filter with the aim to predict the increasingly extreme weather of Surabaya city at the end of 2017. In this research, weather prediction focused on humidity, temperature, and velocity wind with results 5 days later. The prediction of Surabaya city weather using ARIMA method - Kalman filter obtained the smallest error goal (error MAPE) of 0.000014 each for the prediction of humidity, 0.000037 for temperature prediction, and 0.0123 for wind speed prediction." @default.
- W57149851 created "2016-06-24" @default.
- W57149851 creator A5057035512 @default.
- W57149851 date "2018-05-25" @default.
- W57149851 modified "2023-10-18" @default.
- W57149851 title "Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter" @default.
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- W57149851 doi "https://doi.org/10.15642/mantik.2018.4.1.59-67" @default.
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