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PREDIKSI PANEN PERIKANAN DENGAN ALGORITMA GATED RECURRENT UNIT YANG DIOPTIMASIKAN DENGAN ALGORITMA GENETIKA

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Penilaian

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Indonesia is a maritime country with most of the population living near on water areas and water products are a common commodity that is often consumed cheaply and food is therefore one of the primary human needs, so fishery harvest predictions are needed in order to control prices, prepare seeds, so that sales remain stable, consumption is not problematic, etc. The reason for choosing GRU for this prediction is that previously it was common to use classical methods that have been used in econometrics or time series analysis in general, and GRU has fewer operations than LSTM. Instead of training with an optimization algorithm that relies on backpropagation and gradients such as gradient descent, by using metaheuristic optimization in the form of a genetic algorithm on the grounds that the GA does not require gradient information and is expected to avoid local optima, the total average MSE obtained is 9.55%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407001742	T141439	T1414392024	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1414392024

Publisher

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

Collation

xvii, 82 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

003.307

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)

Model dan simulasi komputer
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

SEPTA

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