| dc.description.abstract | Aquatic plants are plants that live in aquatic environments. These plants are often
used as components to decorate aquascapes because of their attractive appearance
and forms. Aquascaping is an art that involves combining aquatic plants,
ornamental fish, wood, rocks, and other decorations within an aquarium to create a
beautifully integrated natural underwater ecosystem. Aquatic plants require light to
grow well, and each type has different light requirements. Therefore, a system was
developed to classify images of aquatic plants. Several methods can be used for
image classification in this field, one of which is the YOLO algorithm. First, data
collection was conducted, gathering 226 images of aquatic plants categorized by
their light requirements. Next, image preprocessing was performed using the
Roboflow platform. Roboflow is capable of data preprocessing, from image data
splitting to augmentation. The result of preprocessing on the Roboflow platform
was a dataset ready for training. Training was carried out using Google Colab
Notebooks with the YOLO method. To find the best model, fine-tuning of the
hyperparameters was also performed. The best-trained model was then used in the
developed system to classify aquatic plants. Test results showed that the YOLO
algorithm could classify the light requirements of aquatic plants with quite high
accuracy, achieving 80.95%. This method can assist aquascape enthusiasts in
selecting aquatic plants based on their light needs. | en_US |
