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Study of the Effect of Physical Parameters on Commercial Hydroponics Based on Internet of Things (IoT): A Case Study of Bok Coy Plants (Brassica rapa) and Water Spinach (Ipomoea Aquatica)

Journal of Mathematical and Fundamental Sciences · Vol. 54 No. 2 (2023) · hlm. 275–289

DOI
10.5614/j.math.fund.sci.2022.54.2.5
ISSN
2338-5510, 2337-5760
Terbit
2023-04-17
Penerbit
Directorate for Research and Innovation (DRI) ITB
Bahasa
eng

Abstrak

Population growth causes the demand for food to increase. One solution that can be applied is agriculture with hydroponic technology. To increase production efficiency, one must know the physical parameters that most influence the production process. This research used an IoT system to gather accurate and precise measurement data of physical parameters to be used as a dataset for machine learning. The dataset consisted of light intensity, humidity, air temperature, and total dissolved solids (TDS). Plant growth was measured by leaf area of the plant, number of leaves, and plant stem length every 3 to 4 days. The models used in the machine learning process were linear regression, polynomial regression, and random forest regression. The machine learning results showed that the best model for predicting plant growth was random forest regression with an MAE of 8.3% and an R2 of 0.93, for both bok coy and water spinach. The variables that influence growth the most are TDS and light intensity. According to the relationship between TDS gradient and plant growth gradient, the most optimal growth can be achieved by raising the TDS gradient or by maintaining a high TDS, which can be achieved by adding nutrient solution to the tank regularly.

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  • Bandung Institute of Technology
  • National Research and Innovation Agency
  • Universitas Gadjah Mada
  • IPB University
  • Universitas Airlangga
  • National University of Malaysia
  • Telkom University
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  • Organisasi berbeda
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Rekan penulisOrganisasiArtikel bersama
Abdul MuidBandung Institute of Technology4
Agus RisdiyantoNational Research and Innovation Agency3
Noviadi Arief RachmanNational Research and Innovation Agency3
Ahmad FudholiNational University of Malaysia3
Agus JunaediNational Research and Innovation Agency3
Mitra DjamalBandung Institute of Technology3
Rudi DarussalamNational Research and Innovation Agency2
Muhamamad Reza Ramadhani RaharjoBandung Institute of Technology2
Mitra DjamalBandung Institute of Technology2
Anwar MuqorobinNational Research and Innovation Agency1
Bambang SusantoNational Research and Innovation Agency1
Harjono Priyo SantosaNational Research and Innovation Agency1
Erwin SusantoTelkom University1
Dalmasius Ganjar SubagioIndonesian Institute of Sciences1
Muhammad KasimNational Research and Innovation Agency1
Udin KomarudinUniversitas Widyatama1
Wahyu SrigutomoBandung Institute of Technology1
Wahyudi WahyudiUniversitas Gadjah Mada1
Irzaman IrzamanIPB University1
Perdinan PerdinanIPB University1
Irwan MeilanoBandung Institute of Technology1
Retna ApsariUniversitas Airlangga1
Wiwit SuryantoUniversitas Gadjah Mada1
Imam SuyantoUniversitas Gadjah Mada1
Ari SetiawanUniversitas Gadjah Mada1
Heriansyah PutraIPB University1
Herlan DarmawanUniversitas Gadjah Mada1
Maria EvitaBandung Institute of Technology1
Moh YasinUniversitas Airlangga1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journals.itb.ac.id/index.php/jmfs/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Study of the Effect of Physical Parameters on Commercial Hydroponics Based on Internet of Things (IoT): A Case Study of Bok Coy Plants (Brassica rapa) and Water Spinach (Ipomoea Aquatica)</dc:title>
	<dc:creator>Budiman, Maman</dc:creator>
	<dc:creator>Partogi, Efraim</dc:creator>
	<dc:creator>Kristi, Ant. Ardath </dc:creator>
	<dc:creator>Anggara, Prianka</dc:creator>
	<dc:creator>Aminah, Nina Siti</dc:creator>
	<dc:subject xml:lang="en-US">bok coy</dc:subject>
	<dc:subject xml:lang="en-US">hydroponics</dc:subject>
	<dc:subject xml:lang="en-US">IoT</dc:subject>
	<dc:subject xml:lang="en-US">machine learning</dc:subject>
	<dc:subject xml:lang="en-US">water spinach</dc:subject>
	<dc:subject xml:lang="en-US">Physics</dc:subject>
	<dc:description xml:lang="en-US">Population growth causes the demand for food to increase. One solution that can be applied is agriculture with hydroponic technology. To increase production efficiency, one must know the physical parameters that most influence the production process. This research used an IoT system to gather accurate and precise measurement data of physical parameters to be used as a dataset for machine learning. The dataset consisted of light intensity, humidity, air temperature, and total dissolved solids (TDS). Plant growth was measured by leaf area of the plant, number of leaves, and plant stem length every 3 to 4 days. The models used in the machine learning process were linear regression, polynomial regression, and random forest regression. The machine learning results showed that the best model for predicting plant growth was random forest regression with an MAE of 8.3% and an R2 of 0.93, for both bok coy and water spinach. The variables that influence growth the most are TDS and light intensity. According to the relationship between TDS gradient and plant growth gradient, the most optimal growth can be achieved by raising the TDS gradient or by maintaining a high TDS, which can be achieved by adding nutrient solution to the tank regularly.</dc:description>
	<dc:publisher xml:lang="en-US">Directorate for Research and Innovation (DRI) ITB</dc:publisher>
	<dc:date>2023-04-17</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journals.itb.ac.id/index.php/jmfs/article/view/18068</dc:identifier>
	<dc:identifier>10.5614/j.math.fund.sci.2022.54.2.5</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Mathematical and Fundamental Sciences; Vol. 54 No. 2 (2022); 275-289</dc:source>
	<dc:source>2338-5510</dc:source>
	<dc:source>2337-5760</dc:source>
	<dc:source>10.5614/j.math.fund.sci.2022.54.2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journals.itb.ac.id/index.php/jmfs/article/view/18068/6157</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Journal of Mathematical and Fundamental Sciences</dc:rights>
</oai_dc:dc>