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PERBANDINGAN METODE SUPPORT VECTOR MACHINE DAN BACKPROPAGATION NEURAL NETWORK UNTUK MENGKLASIFIKASIKAN KEPRIBADIAN BERDASARKAN CITRA TULISAN TANGAN

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Penilaian

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Personality Classification based on handwriting images was not easy, because every handwriting has a unique pattern. Unique patterns in handwriting, such as the degree of slope and spacing between letters. This study aims to develop software that can classify personality based on writing using the support vector machine and backpropagation neural network method. This study uses 1,000 data with two distribution scenarios, the first is 60% training data and 40% test data, and the second is 70% training data and 30% test data. The data will go through preprocessing, segmentation, and feature extraction before entering the support vector machine and backpropagation neural network methods. Based on the test results, in the second scenario, the support vector machine method with the RBF kernel has an accuracy of 98%, and in the first scenario, the backpropagation neural network method has an accuracy value of 55%, so in conclusion, the performance of the support vector machine method with the RBF kernel is better than the backpropagation neural network method.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307000848	T86846	T868462023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T868462023

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xvii, 137 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.307

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem Pakar
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

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