Forest Plantation Pest and Disease Forecast Model
- 10.2991/icedutech-17.2018.37How to use a DOI?
- forecasting model; forest plantation; nursery; ARIMA; Acacia mangium; Falcataria moluccana;
This research aims to propose a forecast model of pest and disease plantation. The data sample collected by Laboratory of forest health and protection - Faculty of Forestry Universitas Gadjah Mada in the periods of times, so we have time series data of Powdery mildew disease growth which has observed from Acacia mangium nursery. This model combined with the expert system model, and the identification and calculation of damage size and the intensity of damage model. The expert system used for identification of pest and disease on plantation, model of identification used for collecting the data and calculting of a size and the intensity of plantation damage, and forecasting model will be used for seeing a disease growing without treatment. In this manuscript, the forecast model is using Auto-Regressive (AR), Moving Average (MA), and ARIMA method to see how the data sample are suitable and the model is working. We are using order (2,1,0) for AR, MA (0,1,2), and combined method ARIMA (2,1,1) which has better RSS value (0.6219). The model may be used by policymakers to take action if there any disease or pest in the nursery or plantation.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Andri Pranolo AU - Siti Muslimah Widyastuti AU - Azhari Azhari PY - 2017/11 DA - 2017/11 TI - Forest Plantation Pest and Disease Forecast Model BT - Proceedings of the 2017 International Conference on Education and Technology (2017 ICEduTech) PB - Atlantis Press SP - 188 EP - 192 SN - 1951-6851 UR - https://doi.org/10.2991/icedutech-17.2018.37 DO - 10.2991/icedutech-17.2018.37 ID - Pranolo2017/11 ER -