Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter

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....

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Autores principales:	Nurissaidah Ulinnuha, Yuniar Farida
Formato:	article
Lenguaje:	EN
Publicado:	Department of Mathematics, UIN Sunan Ampel Surabaya 2018
Materias:	Weather Prediction, ARIMA, Kalman Filter, Polynomial Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/86d0b4772cc141d3a932e2cdccdd70d4
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spelling	oai:doaj.org-article:86d0b4772cc141d3a932e2cdccdd70d42021-12-02T17:37:08ZPrediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter2527-31592527-316710.15642/mantik.2018.4.1.59-67https://doaj.org/article/86d0b4772cc141d3a932e2cdccdd70d42018-05-01T00:00:00Zhttp://jurnalsaintek.uinsby.ac.id/index.php/mantik/article/view/314https://doaj.org/toc/2527-3159https://doaj.org/toc/2527-3167Season 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.Nurissaidah UlinnuhaYuniar FaridaDepartment of Mathematics, UIN Sunan Ampel SurabayaarticleWeather Prediction, ARIMA, Kalman Filter, PolynomialMathematicsQA1-939ENMantik: Jurnal Matematika, Vol 4, Iss 1, Pp 59-67 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Weather Prediction, ARIMA, Kalman Filter, Polynomial Mathematics QA1-939
spellingShingle	Weather Prediction, ARIMA, Kalman Filter, Polynomial Mathematics QA1-939 Nurissaidah Ulinnuha Yuniar Farida Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter
description	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.
format	article
author	Nurissaidah Ulinnuha Yuniar Farida
author_facet	Nurissaidah Ulinnuha Yuniar Farida
author_sort	Nurissaidah Ulinnuha
title	Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter
title_short	Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter
title_full	Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter
title_fullStr	Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter
title_full_unstemmed	Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter
title_sort	prediksi cuaca kota surabaya menggunakan autoregressive integrated moving average (arima) box jenkins dan kalman filter
publisher	Department of Mathematics, UIN Sunan Ampel Surabaya
publishDate	2018
url	https://doaj.org/article/86d0b4772cc141d3a932e2cdccdd70d4
work_keys_str_mv	AT nurissaidahulinnuha prediksicuacakotasurabayamenggunakanautoregressiveintegratedmovingaveragearimaboxjenkinsdankalmanfilter AT yuniarfarida prediksicuacakotasurabayamenggunakanautoregressiveintegratedmovingaveragearimaboxjenkinsdankalmanfilter
_version_	1718379893778022400

Prediksi Cuaca Kota Surabaya Menggunakan Autoregressive Integrated Moving Average (Arima) Box Jenkins dan Kalman Filter

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