Modeling the activity ratio of soil potassium using machine learning approach

Desi Nadalia; Arief Hartono; Heru Bagus Pulunggono; Bambang Hendro Trisasongko; Widiatmaka Widiatmaka; Muhammad Fuady Emzir

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1412-3606 (Print)

2356-1424 (Online)

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About The Authors

Desi Nadalia
ORCID iD Doctoral Program of Soil Science, Graduate School, IPB University, Bogor
Indonesia

Department of Soil Science and Land Resources, Faculty of Agriculture, IPB University, Bogor, 16680, Indonesia

Arief Hartono
ORCID iD Department of Soil Science and Land Resources, Faculty of Agriculture, IPB University, Bogor
Indonesia

Heru Bagus Pulunggono
ORCID iD Department of Soil Science and Land Resources, Faculty of Agriculture, IPB University, Bogor
Indonesia

Bambang Hendro Trisasongko
ORCID iD Department of Soil Science and Land Resources, Faculty of Agriculture, IPB University, Bogor
Indonesia

Widiatmaka Widiatmaka
ORCID iD Department of Soil Science and Land Resources, Faculty of Agriculture, IPB University, Bogor
Indonesia

Muhammad Fuady Emzir
Department of Control and Instrumentation Engineering, King Fahd University of Petroleum and Minerals, Dhahran
Saudi Arabia

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Keywords Adsorption Agriculture Biochar Biofertilizer Carbon sequestration Climate change Compost Drought Heavy metals Land use Maize Manure Precipitation Salinity Soil characteristics Soil chemical properties Soil fertility Soil pH Soil parameters Soil quality Zeolite

Home > Vol 22, No 2 (2025) > Nadalia

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