TY  - THES
N1  - Dr. Siti Mutmainah, S.Kom, M.Cs.
ID  - digilib78918
UR  - https://digilib.uin-suka.ac.id/id/eprint/78918/
A1  - Hernadhif Rafif Wiryawan, NIM.: 22106050023
Y1  - 2026/07/07/
N2  - Pneumonia is a lung infection that ranks among the leading causes of death in children under five, with mortality rates continuing to rise as children get older. This study proposes a pneumonia classification model based on multimodal imaging that integrates an Evidential Neural Network (ENN) based on the Dempster-Shafer Theory (DST) framework. The model was built through five main stages: data collection, preprocessing, feature extraction using ResNet-34, followed by training the ENN model independently for each modality, and concluding with the combination of mass functions using Dempster?s rule of combination. Model evaluation was conducted using the
PB  - UIN SUNAN KALIJAGA YOGYAKARTA
KW  - pneumonia; multimodal imaging; evidential neural network;  Demspter-Shafer Theory
M1  - skripsi
TI  - KLASIFIKASI PENYAKIT PNEUMONIA DENGAN MODEL FUSI CITRA MULTIMODAL MENGGUNAKAN PENDEKATAN DEMPSTER-SHAFER THEORY
AV  - public
EP  - 60
ER  -