Skripsi

KLASIFIKASI CITRA KEBUN RESOLUSI TINGGI DENGAN MENGGUNAKAN BACKPROPAGATION NEURAL NETWORK BERDASARKAN EKSTRAKSI CIRI

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Penilaian

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Manual classification of garden types is carried out only based on direct visual observation of garden images armed with experience and knowledge gained previously. Many problems arise when the process of classifying garden types is carried out manually, including inaccurate and non-uniform. This is because human vision has weaknesses and limitations. Based on this, this study was made a program to classify garden types based on the extraction of size and shape characteristics with the help of computers that utilize image processing and neural network methods Backpropagation Neural Network. The classification of garden types is carried out on 4 types of gardens, namely chili gardens, long bean gardens, banana gardens, and cucumber gardens. The application of garden type classification is carried out through 5 processes, namely collecting garden image data, extracting the size and shape characteristics of garden image data, conducting data training using Backpropagation Neural Network artificial neural networks and data testing. Trials that have been conducted with 80 training image data and 20 test image data show that the neural network backpropagation model used for machine learning in this study has successfully classified plant species contained in the image of the garden. From the results of aerial photo image data used as a map has a spatial resolution of 2.34 cm/pix.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307003519	T106347	T1063472023	Central Library (Referens)	Available

Detail Information

Series Title

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Call Number

T1063472023

Publisher

Indralaya : Prodi Fisika, Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2023

Collation

xiv, 65 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

530.028 507

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)

Pengolahan dan Analisa Data di Bidang Fisika
Prodi Fisika

Specific Detail Info

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Statement of Responsibility

PITRIA

Other version/related

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