TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 18, No 2: April 2020

PSO optimization on backpropagation for fish catch production prediction

Yuslena Sari (Universitas Lambung Mangkurat)
Eka Setya Wijaya (Universitas Lambung Mangkurat)
Andreyan Rizky Baskara (Universitas Lambung Mangkurat)
Rico Silas Dwi Kasanda (Universitas Lambung Mangkurat)



Article Info

Publish Date
01 Apr 2020

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.

Copyrights © 2020






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...