Multi Classification of Strawberry Leaves Using Support Vector Machine (SVM) Method on Smart Greenhouse Plants Based on Internet Of Things (IoT)

Authors

  • osphanie mentari UNIVERSITAS ISLAM NUSANTARA
  • Agung Surya Wibowo Telkom University https://orcid.org/0000-0001-9709-3888
  • Muhammad Zimamul Adli Electrical Engineering, Universitas Islam Nusantara
  • Agung Muhamad Toha Electrical Engineering, Universitas Islam Nusantara

DOI:

https://doi.org/10.24843/LKJITI.2025.v16.i02.p07

Keywords:

Support Vector Machine (SVM), Machine Learning, Multi-Classification, Strawberry Plants, Smart Greenhouse

Abstract

Strawberry plants, or Fragaria x ananassa, are shrubs in the Rosaceae (rose) family that produce sweet and scented red fruit. Strawberries are high in vitamin C and other minerals. The benefits of growing strawberries in smart greenhouses are one of the hydroponic farming sectors advances. The construction of a smart greenhouse system that can be monitored and controlled automatically simplifies agricultural research, which formerly relied on traditional farming and wet labs with long study timeframes and high expenses. This innovation makes it easier for researchers to study the impact of the Internet of Things (IoT) on strawberry plant growth by using several sensors in the greenhouse and Artificial Intelligence (AI) to save time and money in optimizing strawberry plant growth. Meanwhile, the Support Vector Machine (SVM) algorithm with a multi-classification category on leaves 3, 4, and 5 achieved Precision: 0.96, Recall: 0.95, F1-Score: 0.95, and Accuracy: 0.95. The accuracy level reaches 95%, implying that machine learning can be used in strawberry cultivation to assist hydroponic farmers.

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Published

2025-08-31

How to Cite

[1]
osphanie mentari, A. S. Wibowo, M. Z. Adli, and A. M. Toha, “Multi Classification of Strawberry Leaves Using Support Vector Machine (SVM) Method on Smart Greenhouse Plants Based on Internet Of Things (IoT) ”, LKJITI, vol. 16, no. 02, p. 07, Aug. 2025.