<![CDATA[This research aims to apply the linear regression method as a tool for forecasting aquaculture exchange rates (NTPI) in West Papua province. This research uses Jupyter Notebook as a data processing platform by combining the concepts of data mining and regression analysis. Analysis of fish cultivation data and related factors such as farmer income index, household consumption index, etc. to predict NTPI values. This method can help design policies that support economic growth in the aquaculture sector by optimizing exchange rates. These results show that although predictions provide insight, there are certain limitations when using linear regression models to predict the future. The mean squared error (MSE) is 90.78 so further considerations are needed to improve model accuracy. Nevertheless, this research will provide a basis for the West Papua provincial government to implement more effective measures in the aquaculture sector.]]>
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