Informasi Umum

Kode

25.04.037

Klasifikasi

000 - General Works

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Deep Learning

Dilihat

15 kali

Informasi Lainnya

Abstraksi

<p>Pneumonia is a serious lung infection requiring early, accurate diagnosis. Traditional methods rely on chest X- rays, but interpreting these images can be challenging due to variability in radiologist expertise. This study aims to enhance pneumonia detection using deep learning, specifically MobileNetV2, for its efficiency and potential deployment in resource-limited settings. Transfer learning was applied to reduce training time, while data augmentation (rotation, flipping) was used to increase robustness and reduce overfitting. To balance accuracy and computational demands, different input dimensions (128x128 to 224x224) and hyperparameter tuning were explored for potential real-time use in future settings. Results showed that MobileNetV2 achieved high accuracy, reaching 99% with non-augmented data and an F1- score of 99%. After augmentation, performance slightly declined, with precision dropping to 94.97% and recall to 98.13%. The F1-score decreased from 99.36% to 98.24%. Despite this, the model retained strong recall (95% for normal cases and 98% for pneumonia cases), indicating robust classification. This study uniquely evaluates MobileNetV2&#39;s performance across various input dimensions, demonstrating its feasibility for pneumonia detection, especially in low-resource and mobile settings. Future work will address challenges like class imbalance and further optimization for edge deployment, paving the way for accessible and consistent pneumonia diagnosis in diverse clinical environments, ultimately improving patient outcomes.</p>

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Koleksi & Sirkulasi

Tersedia 1 dari total 1 Koleksi

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Pengarang

Nama FALAH ASYRAF DARMAWAN PUTRA
Jenis Perorangan
Penyunting Untari Novia Wisesty
Penerjemah

Penerbit

Nama Universitas Telkom, S1 Informatika
Kota Bandung
Tahun 2025

Sirkulasi

Harga sewa IDR 0,00
Denda harian IDR 0,00
Jenis Non-Sirkulasi