Penerapan Algoritma Support Vector Regression Pada Peramalan Hasil Panen Padi Studi Kasus Kabupaten Malang - Dhan Adhillah Mardhika; Budi Darma Setiawan; Randy Cahya Wihandika (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Rice is one of the important resources in human life, in several surveys it was found that more than 59% of the world's population used rice from rice as food staple. But in another theory stated that the human population will continue to develop exponentially while it is difficult to be followed by the growth of food products, especially in this case rice. Support Vector Regression (SVR) method is a method that will be used in this study, this method has been used in several previous studies such as forecasting gold prices and forecasting electricity consumption. In this study we will focus on testing whether the Support Vector Regression (SVR) method is suitable for use in predicting rice yields, using a number of predetermined parameters, and by applying changes to the parameters, namely the number of iterations, Complexity, Epsilon, Sigma, cLR , Lambda. The best results obtained in this study reached MAPE error rate of 10.133%, these results were achieved with the following parameter values, Number of iterations: 50, Complexity: 1, Epsilon: 0.01, Sigma: 1, cLR: 0.1, Lambda: 1