Hernadhif Rafif Wiryawan, NIM.: 22106050023 (2026) KLASIFIKASI PENYAKIT PNEUMONIA DENGAN MODEL FUSI CITRA MULTIMODAL MENGGUNAKAN PENDEKATAN DEMPSTER-SHAFER THEORY. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.
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Text (KLASIFIKASI PENYAKIT PNEUMONIA DENGAN MODEL FUSI CITRA MULTIMODAL MENGGUNAKAN PENDEKATAN DEMPSTER-SHAFER THEORY)
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Text (KLASIFIKASI PENYAKIT PNEUMONIA DENGAN MODEL FUSI CITRA MULTIMODAL MENGGUNAKAN PENDEKATAN DEMPSTER-SHAFER THEORY)
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Abstract
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
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information / Supervisor: | Dr. Siti Mutmainah, S.Kom, M.Cs. |
| Uncontrolled Keywords: | pneumonia; multimodal imaging; evidential neural network; Demspter-Shafer Theory |
| Subjects: | 000 Ilmu Komputer, Ilmu Informasi, dan Karya Umum > 000 Karya Umum > 004 Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Sains dan Teknologi > Informatika (S1) |
| Depositing User: | Muchti Nurhidaya [muchti.nurhidaya@uin-suka.ac.id] |
| Date Deposited: | 09 Oct 2026 09:46 |
| Last Modified: | 09 Oct 2026 09:46 |
| URI: | http://digilib.uin-suka.ac.id/id/eprint/78918 |
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