Issue

Vol. 5, No. 1, February 2020

Optimization Fuzzy Inference System based Particle Swarm Optimization for Onset Prediction of the Rainy Season

https://doi.org/10.22219/kinetik.v5i1.985
Noviandi Noviandi
Universitas Esa Unggul
Ahmad Ilham
Universitas Muhammadiyah Semarang
http://orcid.org/0000-0001-5109-6258

Corresponding Author(s) : Noviandi Noviandi

noviandi@esaunggul.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 5, No. 1, February 2020

Abstract

Rainfall which is occurred in an area explain the Onset Rainy Season (ORS). ORS is a characteristic of the rainy season which is important to know, but the characteristics of the rain itself is very difficult to predict. We use the method of Fuzzy Inference System (FIS) to predict ORS. Unfortunately, FIS is weak to determine parameters so that influences the working FIS method. In this study, we use PSO to optimize parameter of the FIS method to increase perform of the FIS method for onset prediction of the rainy season with the predictor Sea Surface Temperature Nino 3.4 and Index Ocean Dipole. We used coefficient correlation to determine the relationship between two variables as predictors and RMSE as evaluate to all methods. The experiment result has shown that the work of FIS-PSO after optimizing produced the good work with the coefficient correlation = 0.57 and RMSE = 2.96 that is the smallest value that is better performance if compared with other methods. It can be concluded that the method proposed can increase the onset prediction of the rainy season.

Keywords

Onset Prediction Coefficient Correlation Fuzzy Inference System
Noviandi, N., & Ilham, A. (2020). Optimization Fuzzy Inference System based Particle Swarm Optimization for Onset Prediction of the Rainy Season. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 5(1), 61-70. https://doi.org/10.22219/kinetik.v5i1.985
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Author Biographies

Noviandi Noviandi, Universitas Esa Unggul
Department of Informatics
Ahmad Ilham, Universitas Muhammadiyah Semarang
Health Information Management
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