WEATHER PREDICTION SYSTEM TO SUPPORT CROP PROCESS WITH ANDROID-BASED BACKPROPAGATION ARTIFICIAL NEURAL NETWORK Wiji Setyorini, Moh Ahsan, Amak Yunus, Meme Susilowati & Bagus Rinanto
Universitas Kanjuruhan Malang 1,2,3,5
Universitas Ma Chung Malang 4
Abstract
Information system technology has become an important part of everyday human activities today. But there are some aspects that are still rarely touched by this information system technology. One of them is agriculture. Very rarely information technology that helps agriculture so how to farm farmers today is still the same as before. Even though farming method is not suitable to be applied today, farmers have no alternative solution. The problem most often experienced is the inaccuracy of plants grown with the seasons that occur. So that this application is expected to help farmers in choosing the right crops in accordance with the season that will occur. This study aims to make an application to support the process of planting in Malang district using Backpropagation ANN method. The method used is the calculation of backpropagation neural networks. The data used are sample data from the weather history of Karangploso sub-district from 2009-2018. From the calculation results of this application the MSE error value of 0.0299 is obtained.
Keywords: Backpropagation; Weather Prediction; Planting Process
