ACADSTAFF UGM
| Title | : | ESSPI : Exponential Smoothing Seasonal Planting Index, A New Algorithm For Prediction Rainfall |
| Author | : |
KRISTOKO DWI HARTOMO (1) Prof. Drs. Subanar, Ph.D. (2) Drs. Edi Winarko, M.Sc.,Ph.D. (3) |
| Date | : | 0 2016 |
| Keyword | : | exponential, smoothing, algorithm, seasonal planting index, predictions, accuracy, rainfall, novelty exponential, smoothing, algorithm, seasonal planting index, predictions, accuracy, rainfall, novelty |
| Abstract | : | Exponential smoothing algorithm is a prediction algorithm recommended by the Food and Agriculture Organization. The weakness of the this exponential smoothing prediction algorithm is low accuracy for the prediction of long-term and ineffective in determining the value of smoothing to minimize error. The proposed research is to build a model rainfall prediction using a new algorithm Seasonal Planting Index (ESSPI). By using the algorithm planting seasonal index, rainfall prediction model will generate higher accuracy. The results showed seasonal planting method is the dominant index (5 of 6 test size) have an average accuracy is better than the method of exponential smoothing. Index planting seasonal prediction accuracy of 95.73?tter than the exponential smoothing ? = 0.1 by 56.55%, and exponential smoothing of ? = 55.53. Novelty of this research is new algorithms for classifying data based on seasonal planting index, a new algorithm for determining the smoothing (value), the new fitting algorithm using seasonal planting index, and new algorithms using seasonal rainfall prediction planting index for the determination of the growing season |
| Group of Knowledge | : | Ilmu Komputer |
| Original Language | : | English |
| Level | : | Internasional |
| Status | : |
Published
|