PREDIKSI CUACA MENGGUNAKAN ALGORITMA NEURAL NETWORK BACKPROPAGATION DAN PARTICLE SWARM OPTIMIZATION

MAULANA, AGUNG and Efendi, Rusdi and Januar, Miraswan Kanda (2020) PREDIKSI CUACA MENGGUNAKAN ALGORITMA NEURAL NETWORK BACKPROPAGATION DAN PARTICLE SWARM OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

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Abstract

Information about the weather has an important role for the community in carrying out daily activities. So we need a weather prediction that has a high degree of accuracy. The data used in this study are data from the Sultan Mahmud Badaruddin II Meteorological Station. The data were taken in three years, namely 2015, 2016, and 2017. The data are used in predicting weather by applying the Particle Swarm Optimization and Neural Network Backpropagation methods. The results of the testing process carried out in this study obtained the highest accuracy value of 97.18%. From the accuracy values obtained it can be concluded that the use of the Particle Swarm Optimization and Neural Network Backpropagation methods can be used for weather prediction with a very good degree of accuracy.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	weather prediction, Particle Swarm Optimization, Neural Network Backpropagation.
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 7269 not found.
Date Deposited:	12 Aug 2020 03:33
Last Modified:	12 Aug 2020 03:33
URI:	http://repository.unsri.ac.id/id/eprint/32881

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