Permatasari Silitonga

Ms. Permatasari Silitonga

orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
21 January 2021 in Applied Sciences
Verified
Journal Article
Open access
PDF file
PSPermatasari Silitonga
Permatasari Silitonga
ABAlhadi Bustamam
Alhadi Bustamam
HMHengki Muradi
Hengki Muradi
WMWibowo Mangunwardoyo
Wibowo Mangunwardoyo
BDBeti Ernawati Dewi
Beti Ernawati Dewi
In Indonesia, dengue has become one of the hyperendemic diseases. Dengue consists of three clinical phases—febrile phase, critical phase, and recovery phase. Many patients have died in the critical phase due to the lack of proper and timely treatment. Therefore, we developed models that can predict the severity level of dengue based on the laboratory test results of the corresponding patients using Artificial Neural Network (ANN) and Discriminant Analysis (DA). In developing the models, we used a very small dataset. It is shown that ANN models developed using logistic and hyperbolic tangent activation function with 70% training data yielded the highest accuracy (90.91%), sensitivity (91.11%), and specificity (95.51%). This is the proposed model in this research. The proposed model will be able to help physicians in predicting the severity level of dengue patients before entering the critical phase. Furthermore, it will ease physicians in treating dengue patients early, so fatal cases or deaths can be avoided.