Skripsi

PENINGKATAN KINERJA SISTEM DETEKSI BATU GINJAL PADA CITRA CT SCAN MENGGUNAKAN ALGORITMA YOLOv8 DENGAN MODIFIKASI BACKBONE LAYER

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Penilaian

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Kidney stones are a condition that can interfere with kidney function and if left untreated can increase the risk of various health problems, such as chronic kidney disease, end-stage renal failure, cardiovascular disease, diabetes, and hypertension. Therefore, it is important for sufferers to take early prevention by detecting kidney stones in order to prevent serious complications in the future. In this study, kidney stone detection was carried out on CT Scan images using the YOLOv8 (You Only Look Once) algorithm. To obtain the best accuracy results, this study will compare the results of the model using the default YOLOv8 architecture with the modified architecture. Modification of the YOLOv8 backbone architecture was carried out by dividing it into three separate models, where each model only has four layers with a different number of channels depending on the model used. Based on the evaluation of the testing dataset, it was found that model 3 with batch 64 was the best model with a precision value of 0.994, recall of 0.965, mAP50 of 0.987, and mAP50-95 of 0.771

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507005407	T182778	T1827782025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1827782025

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xiv, 61 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

006.370 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Deteksi Batu Ginjal

Specific Detail Info

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Statement of Responsibility

KA

Other version/related

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