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All Journal Media Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan
Alawiyah, Mutik
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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GSTARI-ARCH MODEL AND APPLICATION ON POSITIVE CONFIRMED DATA FOR COVID-19 IN WEST JAVA Alawiyah, Mutik; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
MEDIA STATISTIKA Vol 14, No 2 (2021): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.14.2.146-157

Abstract

Time series model that is commonly used is the Box-Jenkins based time series model. Time series data phenomena based on Box-Jenkins can be combined with spatial data, it is called the space time model One model based on Box-Jenkins model with heterogeneous location characteristics is the Generalized Space Time Autoregressive Integrated (GSTARI) model for a model that assumes data is not stationary or has a trend. This paper discusses the development of the GSTARI model with the assumption that the error variance is not constant which is applied to positive data confirmed by Covid-19 in West Java Province, especially in 4 regencies/cities that have cases in the high category from 6 March 2020 until 31 December 2020. Four regencies/cities are Depok City, Bekasi City, Bekasi Regency, and Karawang Regency. Parameter estimation method for the assumption of non-constant error variance can use Autoregressive Conditional Heteroscedasticity (ARCH) method. GSTARI-ARCH modeling procedure followed three Box-Jenkins stages, namely the identification process, parameter estimation and checking diagnostic. Application of the GSTARI-ARCH Model to Covid-19 positive confirmed data in 4 regencies/cities has a minimum value of RMSE in Bekasi City. The plot of forecast results for the four regencies/cities has a similar pattern to the actual data only applicable for a short time for 1-2 days.
MODEL SPACE TIME AUTOREGRESSIVE INTEGRATED (STARI) UNTUK DATA DEBIT AIR SUNGAI CITARUM DI PROVINSI JAWA BARAT Alawiyah, Mutik; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 1 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (911.908 KB) | DOI: 10.30598/barekengvol14iss1pp147-158

Abstract

Rainfall in West Java during the rainy season is quite high. This causes the area around the watershed to experience flooding. However, in the dry season the Citarum watershed experiences drought. Changes in the Citarum river water discharge from time to time is not only influenced by time but also influenced by the location around it. To forecast the Citarum river water discharge data, the Space Time Autoregressive Integrated (STARI) model can be used. In this study, the STARI model was applied to the Citarum river water discharge data at all four observation sites. Based on the stationary data, it showed that the data is not stationary, so the differencing process must first be done 1 time. The identification of the order of the AR model was one because the PACF plot was truncated in lag 1. The spatial lag used in this study was the spatial lag of order 2, so the Citarum river water discharge could be predicted with the STARI model. Estimation of STARI) model parameters with a uniform weight matrix was ​estimated by the MLE method with the help of R and S-Plus 8.0 softwares. STARI model with MAPE less than 10% was used for predicting Citarum river water discharge data for the four observation locations, thus the STARI model can be recommended to predict Citarum river water discharge data.
Co-Authors Budi Nurani Ruchjana Kusuma, Dianne Amor