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Image of PERBANDINGAN PADA METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION DAN LEARNING VECTOR QUANTIZATION UNTUK MEMPREDIKSI HASIL PANEN TANAMAN JAGUNG(STUDI KASUS: DAERAH MUARADUA)

Text

PERBANDINGAN PADA METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION DAN LEARNING VECTOR QUANTIZATION UNTUK MEMPREDIKSI HASIL PANEN TANAMAN JAGUNG(STUDI KASUS: DAERAH MUARADUA)

Agustin, Urmila - Personal Name;

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In Indonesia, corn has a good opportunity to be developed in the economy because corn is a source of carbohydrates and a staple food after rice and as animal feed. In predicting corn yields, this is useful for measuring the productivity level of maize plants which is related to the level of maize fertility in South OKU. The method that succeeded in producing the best predictions was an artificial neural network. In this study, a prediction system using Backpropagation and Learning Vector Quantization methods is made, each of these methods has several advantages and advantages, so a comparison of the two methods is carried out to see the output of the best corn plant predictions that have the best accuracy results in making predictions. The data used is secondary data, taken from the Sumber Jaya Agricultural Extension Center, Muaradua, starting from February to November 2021 in 14 villages in Muaradua. In this study, the prediction method that produces the best value is Backpropagation, because the accuracy of the Backpropagation method is 78,57% with an error of 0,2134. Meanwhile, in the Learning Vector Quantization method, the accuracy obtained is only 58,56% with an error of 0,4142. Thus, in predicting maize crop yields for the Muaradua area, it is better to use the Backpropagation method because it provides more accurate predictions than Learning Vector Quantization. Keywords: Backpropagation, Corn, Learning Vector Quantization, Prediction.


Availability
Inventory Code Barcode Call Number Location Status
2207002271T74094T740942022Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T740942022
Publisher
Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022
Collation
xv, 116 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.607
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Jurusan Teknik Informatika
Jaringan Komunikasi Komputer
Specific Detail Info
-
Statement of Responsibility
SEPTA
Other version/related

No other version available

File Attachment
  • PERBANDINGAN PADA METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION DAN LEARNING VECTOR QUANTIZATION UNTUK MEMPREDIKSI HASIL PANEN TANAMAN JAGUNG(STUDI KASUS: DAERAH MUARADUA)
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