<![CDATA[This research aims to produce a comparative level of sensitivity accuracy between fuzzy time series and artificial neural network methods in weather forecasting. The background to the problem identified is that weather conditions are always changing, so a system development is needed to help obtain accuracy values from weather forecasts by paying attention to the sensitivity of the comparison results between the two methods. The research results show that the Artificial Neural Network is effective in providing weather forecast values according to existing datasets, while the Fuzzy Time Series is able to produce sensitivity accuracy values based on existing datasets. This research also reveals that both methods are quite good in determining accuracy results on weather forecast sensitivity to meet user needs. The conclusion of this research is that both methods can provide the right solution for the development of a weather forecasting system that can be used by users.]]>
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