Abstract:
Global climate change is an issue that is enough to grab the attention
of the world community. This is mainly because of the impact it has on human
life. The impact that is felt also occurs in waters on the South Kalimantan
region. This is of course can disrupt the productivity of fish in the marine
waters of South Kalimantan. This study aims to make fish catch production
prediction models based on climate change in the South Kalimantan Province
because the amount of productivity of marine fish has fluctuated. This study
uses climate data as input and fish production as output which is divided into
two, namely training and testing data. Then the prediction is conducted using
Backpropagation method combined with Particle Swarm Optimization
method. The results of the study produced a prediction model with RMSE
of 0.0909 with a combination of parameters used, namely, C1: 2, C2: 2, w: 0.7,
learning rate: 0.5, Momentum: 0.1, Particles: 5, and epoch: 500. While
the model used when predicting testing data produces RMSE of 0.1448.
Keywords:
Backpropagation
Climate change
Fish production prediction
Particle swarm optimization
RMSE
