Rochman, Eka Mala Sari and Miswanto, Miswanto and Suprajitno, Herry and Rachmad, Aeri and Nindyasari, Ratih and Rachman, Fika Hastarita (2022) COMPARISON OF LSTM AND GRU IN PREDICTING THE NUMBER OF DIABETIC PATIENTS. In: 2022 IEEE 8th Information Technology International Seminar (ITIS), October 19 – 21, 2022, Surabaya, Indonesia.

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Abstrak

Diabetes is one of the chronic diseases that many people have. This diabetes disease experienced a significant increase during the pandemic, which could cause numerous deaths. One way to help hospitals prevent too many diabetic patients is to predict the number of diabetic patients. We used the LSTM (Long Short-Term Memory) method to predict diabetic patients. The study was conducted using patient data from the Modopuro Health Center, Mojokerto Regency. The prediction process manually calculates the data, then looks for the correlation of the data according to the LSTM method, namely identifying the autocorrelation coefficients at two to three different time lags. The data observed is daily from January 2, 2021, to April 20, 2022, with as many as 345 data. From the calculation results, the RMSE value is 3.184, while the GRU produces an RMSE of 1.727. It concluded that the GRU could better predict the number of visits of diabetic patients in internal medicine polyclinics.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Teknologi > Teknologi (umum) > Komunikasi informasi teknik
Program Studi:	Fakultas Teknik > S1 Teknik Informatika
Depositing User:	Mrs Ratih Nindysari
Date Deposited:	17 Jul 2023 23:28
Last Modified:	18 Jul 2023 00:34
URI:	http://eprints.umk.ac.id/id/eprint/18688

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