Repository Universitas Pakuan

Detail Karya Ilmiah Dosen

Ririn L, Fitria Virgantari, Ani Andriyani

Judul : DETERMINING BEST SPACE WEIGHT ON GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) MODEL TO PREDICT MINERAL WATER CONSUMPTION IN KABUPATEN BOGOR

Abstrak :
GSTAR model is the development of the Space Time Autoregressive (STAR) model that commonly used for spatial time series data. STAR model assumes for locations with homogeneous characteristics. While GSTAR model can caught a phenomenon with locations that have heterogeneous characteristics, because the parameters for each location different from each other. One of the problem in space time modelling is choosing the space weights. The better space weights will give the better model. This research aim to determine the best space weights in a spesific GSTAR model among uniform weight, distance inverse weight, and cross correlation beetween locations weight. The best space weight will give the smallest Root Mean Square Error (RMSE). Data used in this study is mineral water consumption data in four location in Kabupaten Bogor, namely Ciawi, Cibinong, Cileungsi, and Citeureup on year 2016-2017. Result show that distance inverse weight is the best weight for model GSTAR (11). Acoording to the model with the best weight, prediction of mineral water consumption on 2018 are 481,77 gallon in Ciawi ; 476,72 gallon in Cibinong; 449,51 gallon in Cileungsi and 378,71 gallon in Citeureup.

Keywords space time modelling, GSTAR, RMSE, mineral water consumption

Tahun : 2019 Media Publikasi : Seminar Internasional

Kategori : Poster No/Vol/Tahun : 0 / 0 / 2019

ISSN/ISBN : 0

PTN/S : Universitas Pakuan Program Studi : MATEMATIKA

Bibliography :
[1] Ruchjana B.N., Borovkova S.A., and Lopuhaa H.P. 2012. Least squares estimation of Generalized Space Time AutoRegressive (GSTAR) model and its properties. American Institute of Physics Conference Proceedings.

[2] Wutsqa, D.W., Suhartono, and B. Sutijo. 2010. Generalized Space-Time Autoregressive Modeling. ICMSA Proceeding.

[3] Anggraeni D. 2013. Aplikasi GSTAR Pada Pemodelan Volume Kendaraan Masuk Tol Semarang. Jurnal Ilmiah Media Statistik, Vol. 6 (2) : 71-80.

[4] Suhartono dan M. R. Atok. 2006. Pemilihan bobot lokasi yang optimal pada model GSTAR. Prosiding Konferensi Nasional Matematika XIII, Universitas Negeri Semarang.

[5] Ruchjana, B.N.: Pemodelan Kurva Produksi Minyak Bumi Menggunakan Model Generalisasi S-TAR. Forum Statistika dan Komputasi, IPB, Bogor. (2002).

[6] Satria I, Yasin H, Suparti. 2015. Proyeksi Data Produk Domestik Bruto (PDB) dan Foreign Direct Investment (FDI Menggunakan Vector Autoregressive (VAR). Jurnal Gaussian, Vol. 4 (4) : 895-905.

[7] Virgantari, F., H. Wijayanti., L.B. Multina. 2014. Kajian Model Almost Ideal Demand System pada Fungsi Konsumsi/Permintaan Pangan Hewani di Indonesia. Prosiding Seminar Nasional Matematika 2014. Universitas Indonesia. Jakarta.

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Detail Karya Ilmiah Dosen

Ririn L, Fitria Virgantari, Ani Andriyani

Judul	:	DETERMINING BEST SPACE WEIGHT ON GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) MODEL TO PREDICT MINERAL WATER CONSUMPTION IN KABUPATEN BOGOR
Abstrak	:	GSTAR model is the development of the Space Time Autoregressive (STAR) model that commonly used for spatial time series data. STAR model assumes for locations with homogeneous characteristics. While GSTAR model can caught a phenomenon with locations that have heterogeneous characteristics, because the parameters for each location different from each other. One of the problem in space time modelling is choosing the space weights. The better space weights will give the better model. This research aim to determine the best space weights in a spesific GSTAR model among uniform weight, distance inverse weight, and cross correlation beetween locations weight. The best space weight will give the smallest Root Mean Square Error (RMSE). Data used in this study is mineral water consumption data in four location in Kabupaten Bogor, namely Ciawi, Cibinong, Cileungsi, and Citeureup on year 2016-2017. Result show that distance inverse weight is the best weight for model GSTAR (11). Acoording to the model with the best weight, prediction of mineral water consumption on 2018 are 481,77 gallon in Ciawi ; 476,72 gallon in Cibinong; 449,51 gallon in Cileungsi and 378,71 gallon in Citeureup. Keywords space time modelling, GSTAR, RMSE, mineral water consumption
Tahun	:	2019	Media Publikasi	:	Seminar Internasional
Kategori	:	Poster	No/Vol/Tahun	:	0 / 0 / 2019
ISSN/ISBN	:	0
PTN/S	:	Universitas Pakuan	Program Studi	:	MATEMATIKA
Bibliography	:	[1] Ruchjana B.N., Borovkova S.A., and Lopuhaa H.P. 2012. Least squares estimation of Generalized Space Time AutoRegressive (GSTAR) model and its properties. American Institute of Physics Conference Proceedings. [2] Wutsqa, D.W., Suhartono, and B. Sutijo. 2010. Generalized Space-Time Autoregressive Modeling. ICMSA Proceeding. [3] Anggraeni D. 2013. Aplikasi GSTAR Pada Pemodelan Volume Kendaraan Masuk Tol Semarang. Jurnal Ilmiah Media Statistik, Vol. 6 (2) : 71-80. [4] Suhartono dan M. R. Atok. 2006. Pemilihan bobot lokasi yang optimal pada model GSTAR. Prosiding Konferensi Nasional Matematika XIII, Universitas Negeri Semarang. [5] Ruchjana, B.N.: Pemodelan Kurva Produksi Minyak Bumi Menggunakan Model Generalisasi S-TAR. Forum Statistika dan Komputasi, IPB, Bogor. (2002). [6] Satria I, Yasin H, Suparti. 2015. Proyeksi Data Produk Domestik Bruto (PDB) dan Foreign Direct Investment (FDI Menggunakan Vector Autoregressive (VAR). Jurnal Gaussian, Vol. 4 (4) : 895-905. [7] Virgantari, F., H. Wijayanti., L.B. Multina. 2014. Kajian Model Almost Ideal Demand System pada Fungsi Konsumsi/Permintaan Pangan Hewani di Indonesia. Prosiding Seminar Nasional Matematika 2014. Universitas Indonesia. Jakarta.
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