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All Journal JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia)
Ni Nengah Dita Adriani
Teknik Informatika, STMIK STIKOM Indonesia, Indonesia
Computer Science & IT

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Analisa Prediksi Time Series Jumlah Kasus Covid-19 Dengan Metode BPNN Di Bali Faska Aris Y K Wadi; putu sugiartawan; Ni Nengah Dita Adriani
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 4 No 1 (2021): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.124

Abstract

The COVID-19 pandemic has not yet subsided. This epidemic has spread to almost all countries in the world. In Indonesia, especially in the province of Bali, which experienced a large number of additional positive cases, recoveries and deaths from COVID-19, an analysis was carried out. The purpose of this analysis is to be able to obtain accuracy in predicting the addition of COVID-19 cases, recoveries and deaths in the province of Bali, predictions are made using the covid-19 time series data used in making predictions. what was done obtained the best and not good prediction accuracy, prediction using one input and one output obtained the best precision model accuracy of 72% and for poor accuracy using three inputs and one output with a prediction model accuracy of 33% in the process Covid-19 predictions in Bali.
Co-Authors Faska Aris Y K Wadi PUTU SUGIARTAWAN