Model Jaringan Syaraf Tiruan dalam Peramalan Kasus Positif Covid-19 di Indonesia

Wirawan Setialaksana (Universitas Negeri Makassar)
Dwi Rezky Anandari Sulaiman (Universitas Negeri Makassar)
Shabrina Syntha Dewi (Universitas Negeri Makassar)
Chairunnisa Ar Lamasitudju (Universitas Negeri Makassar)
Nini Rahayu Ashadi (Universitas Negeri Makassar)
Muhammad Asriadi (Universitas Negeri Makassar)

Jurnal MediaTIK
Volume 3 Issue 2, Mei (2020)

Mitigation steps to control Covid-19 outbreak in Indonesia need to take. One of those step is forecasting the spread of the disease. This study compare two artificial neural network models in catching the pattern of Covid-19 positive total cases in Indonesia. Data Training used in this study is Indonesian total positive cases of Covid-19 from March 2 until May 26. The next 10 days data become data testing to show the model accuracy in predicting Covid-19 total cases. MLP shows a better prediction comparing to ELM.Three different prediction accuracy measurement is used – MAE, MAPE, and RMSE. All of them shows less value in MLP than in ELM.