PREDIKSI CUACA MENGGUNAKAN METODE NEURAL NETWORK

YUNITA YUNITA

Abstract


Weather is an important part of people's daily activities. Therefore, many people who need information atmospheric conditions (weather) is more rapid, complete, and accurate. Accurate weather predictions can be used to solve problems arising from the effects of weather such as drought detection, bad weather, crops and production, energy planning industry, aviation, communications and others. Neural Network method is more efficient in computation is fast and capable of handling the data are not stable in the case of typical weather forecast data. For Weather Prediction with synoptic data input is the data. Several experiments were conducted to obtain the optimal architecture and generate accurate predictions. The results showed the artificial neural network method produces an accuracy value of 72.97%.


Full Text:

PDF

References


Aldrian, E., & Djamil, Y. S. (2008). Application of Multivariate ANFIS For Daily Rainfall Prediction : Influences of Training Data Size. MAKARA, 12(April 2008), 7–14.

Felkin, M. (2007). between N -ary and Binary Problems. Between N-ary and Binary Problems, 1–25.

Han & Kamber. (2006). Data Mining: Concept and Technique (2nd ed). United State America.

Heaton. (2008). Introduction to Neural Network With Java (2nd ed). USA. Heaton Research,Inc.

Hung, N. Q., Babel, M. S., Weesakul, S., & Tripathi, N. K. (2009). An artificial neural network model for rainfall forecasting in Bangkok , Thailand. Hydrolgogy and Earth System Sciences, 1413–1425.

Jong Jek Siang. (2009). Jaringan Syaraf Tiruan & Pemrogramannya Menggunakan MATLAB. Yogyakarta : Andi Yogyakarta.

Kusumadewi, Sri & Hartati, Sri. (2010). Neuro-Fuzzy Integrasi Sistem Fuzzy & Jaringan Syaraf. (2nd ed). Yogyakarta: Graha Ilmu.

Liu, H., Member, S., Yu, L., & Member, S. (2005). Algorithms for Classification and Clustering. IEEE Transaction on Knowledge and Data Engineering, 17(April 2005), 491–502.

Pallavi, V. P., Vaithiyanathan, V., & Ph, D. (2013). Combined Artificial Neural Network and Genetic Algorithm for Cloud Classification. International Journal of Engineering Research & Technology (IJET), (May), 787–794.

Radhika, Y., & Shashi, M. (2009). Atmospheric Temperature Prediction using Support Vector Machines. International Jurnal Of Computer Theory and Engineering, 1(April), 55–58. doi:10.7763/IJCTE.2009.V1.9

Simeonov, I., Kilifarev, H., & Ilarionov, R. (2007). Algorithmic realization of system for short-term weather forecasting. Proceedings of the 2007 international conference on Computer systems and technologies - CompSysTech ’07, 1.

Solaimani, K. (2009). Rainfall-runoff Prediction Based on Artificial Neural Network ( A Case Study : Jarahi Watershed ). IDOSI Publication, 5(6), 856–865.

Vercellis, C. (2009). Business Intelligence: Data Mining and Optimization for Decision Making. Wiley.

Winarso.(2002). Pemikiran dan Praktek Perencanaan dalam Era Tranformasi di Indonesia. Bandung: Departemen Teknik Planologi ITB.




DOI: https://doi.org/10.31294/p.v17i1.742

Copyright (c) 2016 Paradigma



ISSN2579-3500

Dipublikasikan oleh LPPM Universitas Bina Sarana Informatika

Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Kota Jakarta Pusat, DKI Jakarta 10450
Telepon: 021-21231170, ext. 704 / 705
Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License