Forecasting Climate Change Patterns to Improving Rice Harvest Using SVR for Achieving Green Economy - Juliandy, Carles; Kelvin, Kelvin; Halim, Apriyanto; Pipin, Sio Jurnalis; Sinaga, Frans Mikael; Lestari, Wulan Sri (Indonesian Journal of Artificial Intelligence and Data Mining, 2024)
The consistently declining rice harvest will cause several economic and environmental problems. The unstable and unpredictable climate change was believed as the main problem of the declining rice harvest. We proposed a method for forecasting climate change to help the farmer in their rice cultivation. We used Support Vector Regression (SVR) to improve algorithm steps such as normalizing the data and applying an Adaptive Linear Combiner (ALC) to optimize the dataset before we processed it with the algorithm. Our model gets 95% accuracy as measured with the confusion matrix. We believe our model will help the farmers in their rice cultivation with good climate forecasting. A further benefit of this research we belief that with the well-forecasted climate, the usage of pesticides will decrease and will help the vision of the Indonesian government with a green economy