CD Skripsi

Klasifikasi Kematangan Tandan Buah Segar Kelapa Sawit Menggunakan Pencitraan Multispektral Dan Jaringan Syaraf Tiruan (Jst) Berbasis Python

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ABSTRACT
The multispectral imaging system can be used in sorting and grading fruit quickly and
non-destructively. In this study, multispectral imaging system is used as a part of
sorting and grading fruit system for oil palm fresh fruits bunches. The multispectral
imaging system uses filter wheels with 8 band pass filters consisting of wavelengths of
520,680,740,770,800,830 and 880 nm. This study aims to classify the ripeness of oil
palm FFB using the multispectral imaging system and artificial neural network (ANN).
This ANN was built in order to classify two ripeness levels, under ripe and ripe. The
multispectral images for the training process are 76 and 22 used for testing process.
The process of training and testing were done to get the desired ANN model. The ANN
results show that the ANN model is successfully classified with the truth (true) 15 of
the 22 available data and reaches an accuracy of 68.2%. These results show that
multispectral imaging system is potensial for classifying the ripeness level of oil palm
FFB.
Keyword: Multispectral imaging, filterwheel, band pass filter, sorting and grading, oil
palm FFB, Artitificial Neural Network (ANN)

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

03 01. 121 (0024)

Penerbit

Pekanbaru : Universitas Riau – FMIPA – Fisika., 2021

Deskripsi Fisik

ix, 79 hlm.; ill.: 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

03 01. 121 (0024)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

FISIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

ELFITRA

Versi lain/terkait

Lampiran Berkas

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