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Abstract
The wider sea area causes greater evaporation of water in Indonesia. In addition, these conditions have an impact on the season that Indonesia has. Indonesia’s high rainfall disrupts human activities. As a result, it is very important to detect cumulonimbus clouds using satellite imagery. The satellite image used is intended to be taken two values of the characteristics possessed. Characteristics taken are average cover and average cloud temperature. Previous studies predicting rain were only done using observational data taken at the height of 10 meters. This research predicts using satellite imagery that represents the cloud peak temperature value. Furthermore, the classification of data is done using backpropagation. The results of the classification process using backpropagation obtained the best results on the distribution of 80% training data and 20% testing data, with the activation function logging in the hidden layer and that the output layer. The results obtained indicate the accuration rate of 88,283%.
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Details
1 Departement of Mathematics, UIN Sunan Ampel Surabaya, Surabaya, Indonesia
2 Weather Modification Technical Unit, Agency for the Assessment and Application of Technology (BPPT), Jakarta, Indonesia
3 Departement of Mathematics Education, University of Riau Islands, Batam, Indonesia
4 Departement of Environmental Engineering, UIN Sunan Ampel Surabaya, Surabaya, Indonesia
5 Departement of Information System, UIN Sunan Ampel Surabaya, Surabaya, Indonesia
6 Departement of Architecture, UIN Sunan Ampel Surabaya, Surabaya, Indonesia
7 Departement of Mathematics, Universitas PGRI Ronggolawe, Tuban, Indonesia
8 Forecaster and Analyst, Meteorological Climatological and Geophysics Agency, Surabaya, Indonesia