Jurnal Gaussian
Vol 5, No 4 (2016): Jurnal Gaussian

PEMODELAN SEASONAL GENERALIZED SPACE TIME AUTOREGRESSIVE (SGSTAR) (Studi Kasus: Produksi Padi di Kabupaten Demak, Kabupaten Boyolali, dan Kabupaten Grobogan)

Aisha Shaliha Mansoer (Unknown)
Tarno Tarno (Unknown)
Yuciana Wilandari (Unknown)

Article Info

Publish Date
28 Oct 2016

Abstract

Generalized Space Time Autoregressive (GSTAR) model is more flexible as a generalization of Space Time Autoregressive (STAR) model which be able to express the linear relationship of time and location. The purpose of this study is to construct GSTAR model for forecasting the rice plant production in the three districts of Central Java. The data which used to contruct the model is quarterly data of rice plant production in Demak, Boyolali and Grobogan from 1987 through 2014. According to the empirical study result using GSTAR model with uniform weight, binary weight, inverse distance wight, and normalized cross correlation weight, GSTAR (31)-I(1)3 with uniform weight is the optimal model. The model shows that every location is influenced by the location itself. Keywords :  GSTAR, Space Time, uniform weight

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Journal Info
Jurnal Gaussian
Website

Abbrev

gaussian

Publisher

Universitas Diponegoro

Subject

Other

Description

Jurnal Gaussian terbit 4 (empat) kali dalam setahun setiap kali periode wisuda. Jurnal ini memuat tulisan ilmiah tentang hasil-hasil penelitian, kajian ilmiah, analisis dan pemecahan permasalahan yang berkaitan dengan Statistika yang berasal dari skripsi mahasiswa S1 Departemen Statistika FSM ...