Climate Forecasting uses Backpropagation Algorithm Artificial Neural Network Model For Agricultural Planning in Gowa Regency
Ainun Ayu Lestari and Ahmad Munir
Universitas Hasanuddin
Abstract
Climate is defined as the average size and variability of the relevant quantities of certain variables over a period of time with a period of time from monthly to annual or millions of years. This study aims to develop climate 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 1975-2018 in Pallangga sub-district, 1992-2018 in Bontomarannu sub-district and 1997-2018 in Bontonompo sub-district. The results showed that the climate classification according to Oldeman in Bontomarannu sub-district was in the B3 climate type suitable for planting rice crops twice and crops once a year while Pallangga sub-districts and Bontonompo sub-districts were in C3 climate type suitable for planting one-time rice crops and crops twice in one year.
Keywords: Climate, Artificial Neural Network, Backpropagation, Cropping Pattern
Topic: Climate Change