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Algorithm Implementation With Ensemble Learning On Weather Forecast Ira Ramadhaniyati; Marlianawati Khodijah; Moh. Ilham Sahrulkhan
International Journal of Smart Systems Vol. 1 No. 1 (2023): February
Publisher : Etunas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijss.v1i1.4

Abstract

Weather conditions are vital in the continuation of human life. Knowing weather conditions became crucial because almost all human life is connected to it. From agriculture, plantations, even to human activities. Therefore, the method of a weather forecast is required for information on today's weather conditions as well as in the future. The purpose of these weather forecasts is simply so that people can use this for survival. Normally we can tell weather conditions from rainfall, temperature and wind speed. The issue, however, is how to determine accurate weather predictions and can be easily used by the general public. In the study, selecting learning ensemble to calculate existing data groups by involving multiple algorithms to find average accuracy and determine which methods work most optimally. As for research results it is expected to be the basis for building weather forecast applications. Accuracy results at 81.21% and mse 18.79%.