Skripsi

KLASIFIKASI LUKA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK PADA APLIKASI MOBILE DENGAN MODEL INCEPTION V3

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Penilaian

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A wound is damage that occurs to body tissue. Effective wound treatment requires a quick initial diagnosis, but often the process of manual wound diagnosis by medical personnel is not always efficient and takes quite a long time. In this research, the author developed an application to classify types of wounds using the Convolutional Neural Network (CNN) method and the Inception V3 model in a mobile application. The types of wounds categorized in this study include abrasions, bruises, burns, torn wounds, ingrown nails, lacerations and stab wounds. The data used in this research amounted to 3.150 data in image format, with a training data ratio of 80% and testing data of 20%. The results of this research are an average accuracy value of 96.82%, precision of 90.29%, recall of 89.52%, and f1-score of 89.52%. In addition, the application performance results were obtained with an average user interface assessment of 81.2%, an assessment of the ease of use of the application of 82.9%, an assessment of the speed of the classification process of 82.9%, and an assessment of the accuracy of the classification results of 75.1%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407000565	T137968	T1379682024	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1379682024

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xv, 72 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.650 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Jaringan Komunikasi Komputer
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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