Spatially Filtered Ridge Regression Modeling to Find Out the Rice Production Factors in East Java, Indonesia

Authors

  • Vita Dewi Islami Universitas Brawijaya
  • Rahma Fitriani Universitas Brawijaya
  • Henny Pramoedyo Universitas Brawijaya

DOI:

https://doi.org/10.21512/commit.v14i2.6665

Keywords:

Spatially Filtered Ridge Regression, Rice Production, East Java

Abstract

The research aims to model rice production in East Java using the Spatially Filtered Ridge Regression (SFRR) method and ensure that all violations of assumptions are resolved by knowing the direct and indirect effect of predictor variables. The data are secondary data sourced from the publication of Badan Pusat Statistik containing provincial food crop agriculture statistics in East Java and the 2018 publication of Dinas Pertanian Jawa Timur (literally translated as Agriculture Department of East Java). The data analysis process is done by RStudio and ArcMap 10.3 software. In the research, the observation unit is 38 regencies or cities in East Java. The analysis results show that SFRR with queen contiguity weighting can overcome spatial autocorrelation and multicollinearity in rice production data in East Java. As for the established model, the variables of rice field area, urea fertilizer, Phonska fertilizer, SP-36 fertilizer, and tractor have a significant effect on rice production. However, ZA fertilizer has no significant effect on rice production. Then, a large comparison of direct and indirect impacts for each predictor variable is also generated. Generally, direct impacts are greater than indirect impacts.

Dimensions

Plum Analytics

Author Biographies

Vita Dewi Islami, Universitas Brawijaya

Magister Student of Statistics Brawijaya University

Rahma Fitriani, Universitas Brawijaya

Department of Statistics

Henny Pramoedyo, Universitas Brawijaya

Department of Statistics

References

A. Rohman and A. D. Maharani, “Proyeksi kebutuhan konsumsi pangan beras di Daerah Istimewa Yogyakarta,” Caraka Tani: Journal of Sustainable Agriculture, vol. 32, no. 1, pp. 29–34, 2017.

W. R. Tobler, “A computer movie simulating urban growth in the Detroit region,” Economic Geography, vol. 46, no. Sup1, pp. 234–240, 1970.

Mahananto, S. Sutrisno, and C. F. Ananda, “Faktor-faktor yang mempengaruhi produksi padi studi kasus di Kecamatan Nogosari, Boyolali, Jawa Tengah,” WACANA, Jurnal Sosial dan Humaniora, vol. 12, no. 1, pp. 179–191, 2009.

D. N. Gujarati and P. D. C, Basic econometrics. McGraw-Hill Irwin, 2009.

L. Anselin, Spatial econometrics: Methods and models. Springer Science & Business Media, 2013, vol. 4.

C. Fan, S. J. Rey, and S. W. Myint, “Spatially Filtered Ridge Regression (SFRR): A regression framework to understanding impacts of land cover patterns on urban climate,” Transactions in GIS, vol. 21, no. 5, pp. 862–879, 2017.

A. D. P. Sari and W. S. Winahju, “Pemodelan faktor-faktor yang memengaruhi produksi padi di Jawa Timur,” Jurnal Sains dan Seni ITS, vol. 5, no. 2, pp. 414–419, 2016.

F. Arnanda and A. Karim, “Pemodelan produksi padi di Provinsi Jawa Tengah dengan pendekatan spatial econometrics,” Jurnal Statistika Universitas Muhammadiyah Semarang, vol. 4, no. 2, pp. 20–27, 2016.

R. Q. Muslim, B. Barus, and K. Munibah, “Analisis spasial indeks pertanaman dan produktivitas padi sawah di Dusun 1 Desa Purwasari, Kabupaten Bogor,” Skripsi, Departemen Ilmu Tanah dan Sumber daya Lahan, Fakultas Pertanian, Bogor Agricultural University (IPB), 2017.

J. P. LeSage and R. K. Pace, An introduction to spatial econometrics. Boca Raton: Chapman & Hall/CRC, 2009.

G. Arbia, Spatial econometrics: Statistical foundations and applications to regional convergence. Germany: Springer Science & Business Media, 2006.

R. Fitriani and A. Efendi, Ekonometrika spasial terapan dengan R. Malang: UB Press, 2019.

N. U. Putri, Maiyastri, and H. Yozza, “Permasalahan autokorelasi pada analisis regresi linier sederhana,” Jurnal Matematika UNAND, vol. 2, no. 2, pp. 26–34, 2013.

H. Pramoedyo, Statistika inferensia terapan. Malang: Danar Wijaya, 2013.

M. H. Kutner, C. J. Nachtsheim, J. Neter, and W. Li, Applied linear statistical models. Irwin, 2004.

Kementerian Pertanian Republik Indonesia. (2018) Tabel 2.1.3. Produksi padi menurut provinsi, 2014-2018. [Online]. Available: https://www.pertanian.go.id/Data5tahun/TPATAP-2017(pdf)/20-ProdPadi.pdf

Downloads

Published

2020-11-23
Abstract 418  .
PDF downloaded 354  .