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Jurnal
Sistem Penyiraman Otomatis Tanaman Semusim Berbasis Jaringan Saraf Tiruan Multilayer Perceptron
Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali)
ISSN 2502-5562
Published 2022-02-27
Publisher Universitas Halu Oleo
Language eng
Abstract
In general, farmers water plants when the conditions are met, such as dry soil, no rain, and cold temperatures. One of the efficient ways to control it is to use an artificial neural network-based automatic plant watering system. The purpose of this study was to determine the success of artificial neural networks as decision-makers to water plants automatically. The stages of designing an automatic watering system based on an artificial neural network were to build software including artificial neural network modeling and Arduino microcontroller programming, automatically watering tools, evaluating tool performance, and testing tools in real-time. The test results show that the artificial neural network-based automatic plant watering system can water plants according to the given input pattern. The artificial neural network structure obtained is three neurons in the input layer, eight neurons in the hidden layer, and one neuron in the output layer. The artificial neural network-based automatic plant watering system succeeded in automatically watering two areas of land that the success rate is a 100%.Keyword— Automatic Watering, Microcontroller, ANN, Annual Crops.
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24 authors ·
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Metadata source: OAI-PMH (metadata jurnal) https://ojs.uho.ac.id/index.php/JFE/oai,
first harvested 31 Okt 2026,
last seen 1 Nov 2026.
Original metadata (oai_dc)
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<dc:title xml:lang="en-US">Sistem Penyiraman Otomatis Tanaman Semusim Berbasis Jaringan Saraf Tiruan Multilayer Perceptron</dc:title>
<dc:creator>Zakaria, Mamang</dc:creator>
<dc:creator>Pagiling, Luther</dc:creator>
<dc:creator>Siti Nur Alam, Wa Ode</dc:creator>
<dc:subject xml:lang="en-US">Automatic Watering, Microcontroller, ANN, Annual Crops.</dc:subject>
<dc:description xml:lang="en-US">In general, farmers water plants when the conditions are met, such as dry soil, no rain, and cold temperatures. One of the efficient ways to control it is to use an artificial neural network-based automatic plant watering system. The purpose of this study was to determine the success of artificial neural networks as decision-makers to water plants automatically. The stages of designing an automatic watering system based on an artificial neural network were to build software including artificial neural network modeling and Arduino microcontroller programming, automatically watering tools, evaluating tool performance, and testing tools in real-time. The test results show that the artificial neural network-based automatic plant watering system can water plants according to the given input pattern. The artificial neural network structure obtained is three neurons in the input layer, eight neurons in the hidden layer, and one neuron in the output layer. The artificial neural network-based automatic plant watering system succeeded in automatically watering two areas of land that the success rate is a 100%.Keyword— Automatic Watering, Microcontroller, ANN, Annual Crops.</dc:description>
<dc:publisher xml:lang="en-US">Universitas Halu Oleo</dc:publisher>
<dc:contributor xml:lang="en-US"></dc:contributor>
<dc:date>2022-02-27</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
<dc:format>application/pdf</dc:format>
<dc:identifier>https://ojs.uho.ac.id/index.php/JFE/article/view/24050</dc:identifier>
<dc:identifier>10.33772/jfe.v7i1.24050</dc:identifier>
<dc:source xml:lang="en-US">Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali); Vol 7, No 1 (2022): Jurnal Elektroda Vol 7 No 1; 35-45</dc:source>
<dc:source>2502-5562</dc:source>
<dc:source>10.33772/jfe.v7i1</dc:source>
<dc:language>eng</dc:language>
<dc:relation>https://ojs.uho.ac.id/index.php/JFE/article/view/24050/pdf</dc:relation>
<dc:relation>https://ojs.uho.ac.id/index.php/JFE/article/downloadSuppFile/24050/4375</dc:relation>
<dc:rights xml:lang="en-US">Copyright (c) 2022 Mamang Zakaria, Luther Pagiling, Wa Ode Siti Nur Alam</dc:rights>
<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>
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Cite this article
APA 7
Zakaria, M., Pagiling, L., & Siti Nur Alam, W. O. (2022). Sistem Penyiraman Otomatis Tanaman Semusim Berbasis Jaringan Saraf Tiruan Multilayer Perceptron. Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali), 7(1), 35–45. https://doi.org/10.33772/jfe.v7i1.24050
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IEEE
M. Zakaria, L. Pagiling, and W. O. Siti Nur Alam, “Sistem Penyiraman Otomatis Tanaman Semusim Berbasis Jaringan Saraf Tiruan Multilayer Perceptron,” Jurnal Fokus Elektroda : Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali), vol. 7, no. 1, pp. 35–45, 2022, doi: 10.33772/jfe.v7i1.24050.
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