Analisa Implementasi Metode Fuzzy Time Series Jasim pada Prediksi Perkembangan COVID-19 di Indonesia

D. R. Prehanto, Ginanjar Setyo Permadi, Melvin Nurdiansari
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Abstract

The pandemic of COVID-19 that has been going on since March 2020 until now has weakened many sectors in many countries an Indonesia as well. In Indonesia, more than 9,000 people have died because of this pandemic. In the first week, 56 cases of COVID-19 were recorded and the cases continued to increase to more than 2,000 cases per week so that the increasing number of cases could result in a lack of service provision and facilities for medical. This study aims to determine the forecasting scheme and how the development of COVID-19 cases that occur in Indonesia. Fuzzy Time Series Jasim method that is applied to find out how to do forecasts by managing previous data.  This method uses the determination of the width of the interval, the formation of a set from historical data and using of the average based length method. In this method also used grouping and data relations that have been fuzzified. From the method that has been used, it can be seen that the results obtained from the Fuzzy Time Series Jasim method are obtained from the accuracy rate of the accuracy error using MAD of 286. And the error magnitude of the forecasting results with the actual data using MAPE is 2.43%. Where it can be concluded that the use of Fuzzy Time Series Jasim method in this study provides good forecasting results
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分析Jasim的模糊时间方法系列的实施,以预测COVID-19在印度尼西亚的发展
自2020年3月以来一直持续到现在的新冠肺炎大流行也削弱了包括印度尼西亚在内的许多国家的许多部门。在印度尼西亚,有9000多人死于这场大流行。在第一周,记录了56例COVID-19病例,病例继续增加到每周2000多例,因此病例数量的增加可能导致缺乏服务和医疗设施。本研究旨在确定预测方案以及印度尼西亚发生的COVID-19病例的发展情况。模糊时间序列的Jasim方法,是用来找出如何通过管理以前的数据进行预测。该方法采用确定区间宽度,从历史数据中形成一组,并使用基于平均长度的方法。该方法还采用了分组和模糊化的数据关系。从所采用的方法可以看出,模糊时间序列Jasim方法得到的结果是由286的MAD精度误差的正确率得到的。MAPE预测结果与实际数据的误差幅度为2.43%。在哪里可以得出结论,在本研究中使用模糊时间序列Jasim方法提供了良好的预测效果
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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