%0 Thesis
%9 Skripsi
%A Hernadhif Rafif Wiryawan, NIM.: 22106050023
%B FAKULTAS SAINS DAN TEKNOLOGI
%D 2026
%F digilib:78918
%I UIN SUNAN KALIJAGA YOGYAKARTA
%K pneumonia; multimodal imaging; evidential neural network;  Demspter-Shafer Theory
%P 60
%T KLASIFIKASI PENYAKIT PNEUMONIA DENGAN MODEL FUSI CITRA MULTIMODAL MENGGUNAKAN PENDEKATAN DEMPSTER-SHAFER THEORY
%U https://digilib.uin-suka.ac.id/id/eprint/78918/
%X 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
%Z Dr. Siti Mutmainah, S.Kom, M.Cs.