Autoregressive Integrated Moving Average (ARIMA) Sebagai Model Peramalan Kasus Demam Berdarah Dengue

Roro Kushartanti, Maulina Latifah
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Abstract

ARIMA is a forecasting method time series that does not require a specific data pattern. This study aims to analyze the forecasting of Semarang City DHF cases specifically in the Rowosari Community Health Center. The study used monthly data on DHF cases in the Rowosari Community Health Center in 2016, 2017, and 2019 as many as 36 dengue case data. The best ARIMA model for forecasting is a model that meets the requirements for parameter significance, white noise and has the MAPE (Mean Absolute Percentage Error Smallest) value. The results of the analysis show that the best model for predicting the number of dengue cases in the Rowosari Public Health Center Semarang is the ARIMA model (1,0,0) with a MAPE value of 43.98% and a significance coefficient of 0.353, meaning that this model is suitable and feasible to be used as a forecasting model. DHF cases in the Rowosari Community Health Center in Semarang City.
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自回归综合移动平均(ARIMA)作为登革热治疗模型
ARIMA是一种不需要特定数据模式的时间序列预测方法。本研究旨在分析三宝垄市DHF病例的预测,特别是在Rowosari社区卫生中心。该研究使用了罗沃萨里社区卫生中心2016年、2017年和2019年多达36例登革热病例的月度数据。用于预测的最佳ARIMA模型是满足参数显著性、白噪声要求并且具有MAPE(平均绝对百分比误差最小)值的模型。分析结果表明,预测罗沃萨里公共卫生中心三宝垄登革热病例数的最佳模型是ARIMA模型(1,0,0),其MAPE值为43.98%,显著性系数为0.353,这意味着该模型作为预测模型是合适和可行的。三宝垄市Rowosari社区卫生中心的DHF病例。
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CiteScore
1.00
自引率
0.00%
发文量
32
审稿时长
16 weeks
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