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Image of IMPLEMENTASI KLASIFIKASI PRA-KANKER SERVIKS MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK BERBASIS PLATFORM ANDROID

Skripsi

IMPLEMENTASI KLASIFIKASI PRA-KANKER SERVIKS MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK BERBASIS PLATFORM ANDROID

Lubis, Nur Muhammad Erji Ridho - Personal Name;

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Penilaian anda saat ini :  

Cervical cancer is the most common type of cancer in women worldwide. Early classification of pre-cancerous cervical cells is important to prevent the development of more serious cervical cancer. This study proposes the implementation of pre-cancer cervical classification using Convolutional Neural Network (CNN) based on the Android platform. The experimental results show that the CNN model can classify pre-cancerous cervical cells with good accuracy. The best model in the first experiment was obtained using the VGG 19 architecture with an accuracy of 95.50%, while in the second experiment, the best model was obtained using the Xception architecture with an accuracy of 98.98%. Each parameter in the experiment has different accuracy, thus, it is necessary to tune the hyperparameters to obtain maximum accuracy results. The resulting model usually has a large size, thus it needs to be placed inside a server and requires a web service to access the model. In addition, network bandwidth speed also affects the latency testing process. In implementation, the system can run well according to the design that has been made before. In terms of processing time or latency, a private server has better performance than VPS. In the prediction testing, the model built using Torch was faster than using Keras. The implementation of pre-cancer cervical classification using CNN on the Android platform can improve early detection of cervical cancer and speed up access to medical services for the public.


Availability
Inventory Code Barcode Call Number Location Status
2307003480T99840T918882023Central Library (Referens)Available
Detail Information
Series Title
-
Call Number
T918882023
Publisher
Indralaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023
Collation
xiv, 79 hlm.; Ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
005.430 7
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Sistem Operasi
Jurusan Sistem Komputer
Specific Detail Info
-
Statement of Responsibility
FIRA
Other version/related

No other version available

File Attachment
  • IMPLEMENTASI KLASIFIKASI PRA-KANKER SERVIKS MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK BERBASIS PLATFORM ANDROID
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