Peramalan dan deteksi outlier saham perusahaan angkutan laut umum di masa covid-19 dengan pemodelan arima

Ilham Thaib, Gesit Thabrani, Silvia Netsyah
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Abstract

The public sea freight sector is one of the affected by COVID-19. PT. Samudera Indonesia Tbk is one of the sea transportations companies in Indonesia. The ARIMA model in the previous study provided a statistical test with the aim of evaluating the suitability of the model with a p value of less than 0.05 to determine ARIMA by guessing through ACF (Autocorrelation Function) and PACF (Partial Autocorrelation Function) through stationary data. Outlier detection can be done by plotting the residuals from the specified model. Forecasting data for the next 5 days using the ARIMA (3,1,2) model can be seen that the results of forecasting stock price data for PT. Samudera Indonesia Tbk using ARIMA (3,1,2) is within the 95% confidence interval with a forecast value that is close to the actual value. There are outliers that are detected which are related to economic phenomena.Keywords: Forecasting, Covid-19, stock, ARIMA, outlier
公共海运部门是受新冠肺炎疫情影响的部门之一。PT. Samudera Indonesia Tbk是印度尼西亚海上运输公司之一。前面研究中的ARIMA模型提供了一个p值小于0.05的统计检验,目的是评价模型的适用性,通过平稳数据通过自相关函数(ACF)和部分自相关函数(PACF)猜测确定ARIMA。异常值检测可以通过绘制指定模型的残差来完成。使用ARIMA(3,1,2)模型预测未来5天的数据可以看出,使用ARIMA(3,1,2)模型预测PT. Samudera Indonesia Tbk股价数据的结果在95%置信区间内,预测值接近实际值。我们发现了一些与经济现象有关的异常值。关键词:预测,Covid-19,库存,ARIMA,异常值
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