9th Annual International Conference on Industrial Engineering and Operations Management

Application of Spatial Weighting Matrix of GSTAR by Using CLARANS Clustering on Farmer Exchange Rates in 32 Provinces in Indonesia

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Track: Data Analytics and Big Data
Abstract

Generalized Space Time Autoregressive (GSTAR) model was used to model the time series data that had correlation inter-location (space time). In the stage of model identification, spatial weight on GSTAR model shown relations of inter-location, which were weight normalized cross-correlation, binary, uniform, and inverse of distance. Data grouping uses the CLARANS (Clustering Large Application based on Randomized Search) Cluster analysis method, which is a clustering method that involves spatial elements by determining the number of clusters at the beginning where each object has the opportunity to be selected as a cluster center. The data used was secondary data of Farmer Exchange Rates in 32 provinces for 71 months from year 2005 to 2013, which has been obtained from the Economic Indicators published by BPS every month. Model candidates that have been obtained of the data were GSTAR(1;1) and GSTAR(2;1;1).

Published in: 9th Annual International Conference on Industrial Engineering and Operations Management, Bangkok, Thailand

Publisher: IEOM Society International
Date of Conference: March 5-7, 2019

ISBN: 978-1-5323-5948-4
ISSN/E-ISSN: 2169-8767