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

Wirawan Wirawan Setialaksana; Dwi Reski Anandari Sulaiman; Shabrina Syntha Dewi; Chairunnisa Ar Lamasitudju; Nini Rahayu Ashadi; Muhammad Muhammad Asriadi

doi:10.26858/jmtik.v3i1.14389

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

Wirawan Wirawan Setialaksana^(1*), Dwi Reski Anandari Sulaiman⁽²⁾, Shabrina Syntha Dewi⁽³⁾, Chairunnisa Ar Lamasitudju⁽⁴⁾, Nini Rahayu Ashadi⁽⁵⁾, Muhammad Muhammad Asriadi⁽⁶⁾,

(1) Universitas Negeri Makassar
(2) Universitas Negeri Makassar
(3) Universitas Negeri Makassar
(4)
(5) Universitas Negeri Makassar
(6) Universitas Negeri Makassar
(*) Corresponding Author

DOI: https://doi.org/10.26858/jmtik.v3i1.14389

Abstract

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.