文章基本信息

标题：Peramalan Jumlah Kasus Infeksi Saluran Pernafasan Akut (ISPA) pada Laki-Laki Tahun 2019 dengan Metode ARIMA
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作者：Moch. Fitriawan Eka Saputra ; Muhammad Rizky
期刊名称：Jurnal Biometrika dan Kependudukan
印刷版ISSN：2302-707X
电子版ISSN：2540-8828
出版年度：2019
卷号：8
期号：2
页码：138-145
DOI：10.20473/jbk.v8i2.2019.138-145
出版社：Universitas Airlangga
摘要：The ARIMA method is an approach that forms the most powerful model in analyzing time series data, and the studies given are very thorough. This method can be modeling data stationary or not stationary, it can be seen from sine wave shape of the plot ACF. This method is used because obtained the results are better and more accurate. According to WHO, Acute Respiratory Infection (ARI) is an infectious disease that causes can be morbidity and mortality. A four million people die each year. This study used secondary data so that it is categorized as non reactive research. The population were cases of Acute Respiratory Infections (ARI) at Jagir Health Center Surabaya which were recorded in 2013 to 2018 (monthly). The dependent variable is the cases of Acute Respiratory Infection (ARI), while the independent variable is time. The model that was obtained from the ARIMA method is a model (2.0,1). The forecasting result is 354 cases in 2019, the forecasting has increased from 2018 to only 313 cases. It was a suggestion that the forecasting result can be a reference for developing a policy and a new program or improvement in previous program so that the number cases of ARI at the Jagir Health Center can be resolved properly.
其他摘要：The ARIMA method is an approach that forms the most powerful model in analyzing time series data, and the studies given are very thorough. This method can be modeling data stationary or not stationary, it can be seen from sine wave shape of the plot ACF. This method is used because obtained the results are better and more accurate. According to WHO, Acute Respiratory Infection (ARI) is an infectious disease that causes can be morbidity and mortality. A four million people die each year. This study used secondary data so that it is categorized as non reactive research. The population were cases of Acute Respiratory Infections (ARI) at Jagir Health Center Surabaya which were recorded in 2013 to 2018 (monthly). Th e dependent variable is the cases of Acute Respiratory Infection (ARI), while the independent variable is time. The model that was obtained from the ARIMA method is a model (2.0,1). T he forecasting result is 354 cases in 2019, the forecasting has increased from 2018 to only 313 cases. It was a suggestion that the forecasting result can be a reference for developing a policy and a new program or improvement in previous program so that the number cases of ARI at the Jagir Health Center can be resolved properly.
关键词：forecasting; autoregressive intregated moving average; acute respiratory tract infection
其他关键词：forecasting; autoregressive intregated moving average; acute respiratory tract infection