ESSA: Exponential smoothing and spatial autocorrelation, methods for prediction of outbreaks pest in Indonesia
Penulis/Author
Sri Yulianto Joko Prasetyo (1); Prof. Drs. Subanar, Ph.D. (2); Drs. Edi Winarko, M.Sc.,Ph.D. (3); Prof. Dr. Budi S. Daryono, M.Agr.Sc. (4)
Tanggal/Date
2015
Kata Kunci/Keyword
Abstrak/Abstract
Geographically, Indonesia is one of the countries in Asia are at risk of disease pests of rice brown planthoppers or BPH
(Nilaparvata lugen Stal.) through a cycle of long-distance migration along the years following the tropical Monsoon
flow. BPH attacked this country since 1930 until now. It damaged ten thousand hectares of rice and made crop failure.
As anticipated in the future surveillance system is needed that is able to predict the dynamics of migration of BPH
early so that the concentration of BPH endemicity. The focus of the research is to develop a procedure Exponential
Smoothing and Spatial Autocorrelation (ESSA), which includes a mechanism prediction using Exponential Smoothing
method and mechanism analysis of BPH spatial patterns attack using Spatial Autocorrelation method. The research
was conducted through four stages which include: (1) the identification and determination of areas experiencing high
attack BPH in the study area, (2) grouping of BPH data attacks that followed local cropping patterns, (3) the prediction
and analysis of spatial connectivity using the Local Indicator Spatial Association (LISA), and (4) visualization and
interpretation of analytical results. Prototype was built using the programming language R (http://r-cran.project). The
result of the research could be developed as geographical information system (GIS) tool to predict the migration
Rumpun Ilmu
Ilmu Komputer
Bahasa Asli/Original Language
English
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
2_ 2015-IRECOS Scopus-ESSA methods for prediction of outbreak-PSWD.pdf
