Timeseries forecasting for Local Average Temperature in Northern Sumatera Using Long Short-Term Memory Model
DOI:
https://doi.org/10.53842/juki.v5i2.385Keywords:
temperature, trends, forecasting, lstm, timeseriesAbstract
For better management and planning of water resources in a basin, it is important to understand trends and predict average temperature as one of the parameters of weather and climate data. The study of weather trends using normal and local annual average temperature, comparison and observation. In this study, we will analyse the local and normal average temperature data in the city of Medan, based on the observation station in situ. The main objective of this study is to compare the normal temperature with the local station and to predict the temperature data in the city of Medan, North Sumatra by using the long term short term memory model. Based on the result of normal data science of exploring temperature with local temperature correlation, we got the display of training curve, residual plot and the scatter plot are shown using these codes. The good performance of Kualanamu and better than Deliserdang station had MSE value 0.01 and R2 value 0.98, close to zero represents better prediction quality.
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