Penerapan Arima Dan Artificial Neural Network Untuk Prediksi Penderita DBD Di Kabupaten Sragen - Hendra Setiawan; Ema Utami; Hanif Al Fatta (Majalah Ilmiah Bahari Jogja, 2020)
The number of DHF patients in Sragen regency in the last few years continued to increase which was then compounded by seasonal changes. The lack of public awareness of the problem of DHF was caused by ignorance of the public on the dangers of DHF and its spread. Based on existing research, DHF distribution patterns were also influenced by environmental factors such as population movement patterns that were influenced by how well the existing transportation systems and facilities. Based on this fact, the author tries to apply several methods of forecasting the number of DHF sufferers to see whether there is a real influence between how good the transportation system is with the number of DHF sufferers and increase the level of public awareness and facilitate parties who need data on the spread of DHF sufferers in Sragen Regency in the period of required period. The models used in this study are ARIMA, Backpropagation, and Point Estimation models. The prediction process was done by dividing the forecasting process into two based on the dataset used, namely the dataset from 2013 to 2106 for complete data and the dataset from 2010 to 2016 for incomplete datasets due to missing or damaged data. The data used as a dataset were data taken from data on the number of patients in Sragen regency. The forecasting process in this study was carried out by forecasting using the ARIMA and LSTM methods on two prepared datasets.