Geographic Information System for Detecting Spatial Connectivity Brown Planthopper Endemic Areas Using a Combination of Triple Exponential Smoothing - Getis Ord

Abstract

This study aims to develop a GIS application to detect the possible formation of brown planthoppers (BPH) (Nilaparvata lugens.Stal) endemic areas based on spatial trend, hierarchical effects and risks areas caused of spatial connectivity in a particular area. The study was conducted through five stages: (1) the collection and preprocessing of research data, (2) database development, (3) the creation of the component class Exponential Smoothing, Weight Metrics and Getis Ord, (4) development of a Early Warning class and GIS applications, and (5) information visualization in the form of graphs, maps and tables. The results show that the software component in this study; the class prediction engine; Getis Ord class and class early detection function optimally generate predictive, endemic regions and early warning information on the period ahead.