Weather Forecast using Learning Vector Quantization Methods

Siska Andriani (Universitas Pakuan)
Kotim Subandi (Universitas Pakuan)

Procedia of Social Sciences and Humanities
Vol. 1 (2021): Proceedings of the 2nd International Conference On Intelectuals Global Responsibility

Weather forecasting is one of the important factors in daily life, as it can affect the activities carried out by the community. The study was conducted to optimize weather forecasts using artificial neural network methods. The artificial neural network used is a learning vector quantization (LVQ) method, in which artificial neural networks based on previous research are suitable for prediction. The research is modeling weather forecast optimization using the LVQ method. Models with the best accuracy can be used in terms of weather forecasts. Based on the results of the training that has been done in this study produces the best accuracy on the LVQ method which is to produce 72%.