Weather Forecasting Uses Backpropagation Algorithm Artificial Neural Network Model for Agricultural Planning in Three Villages at Three Sub-Districts of Gowa Regency Ainun Ayu Lestari, Ahmad Munir and Suhardi
Weather is a condition of air in a narrow place, which is a condition based on symptoms of temperature, air pressure, humidity, wind, rainfall, sun exposure, cloud conditions, wind speed and others. This study aims to develop weather prediction models that are used for planning agricultural cultivation activities. The method used in predicting climate is Backpropagation Artificial Neural Network technique based on rainfall data in 1996-2019 in Samata Village, 1975-2019 in Julu Bori Village and 2007-2019 in Tete Batu Village. The results showed that the climate classification according to Oldeman in Samata Village dan Julu Bori Village were in the C1 climate type suitable for planting one-time rice crops and crops twice in one year while Tete Batu Village was in the B3 climate type suitable for planting rice crops twice and crops once a year.