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

CommIT (Communication and Information Technology) Journal · Vol. 14 No. 2 (2020) · hlm. 95–102

DOI
10.21512/commit.v14i2.6665
ISSN
2460-7010, 1979-2484
Terbit
2020-11-23
Penerbit
Bina Nusantara University
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

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.

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  • University of Brawijaya
  • Universitas Negeri Surabaya
  • University of Bengkulu
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Rekan penulisOrganisasiArtikel bersama
Ani Budi AstutiUniversity of Brawijaya2
Wigbertus NgabuUniversity of Brawijaya2
Suci AstutikUniversity of Brawijaya2
Naufal Shela AbdilaAfiliasi tidak diketahui2
Rinda Lolita MelanwatiUniversity of Brawijaya1
Eni SumarminingsihUniversity of Brawijaya1
Danang AriyantoUniversitas Negeri Surabaya1
Novi Nur AiniUniversity of Brawijaya1
Rahma FitrianiUniversity of Brawijaya1
Achmad EfendiUniversity of Brawijaya1
Fachri FaisalUniversity of Bengkulu1
Atiek IrianyUniversity of Brawijaya1
Sativandi RizaUniversity of Brawijaya1
Suci Astutik urul Atiqah RomliAfiliasi tidak diketahui1
Agus YarcanaUniversity of Brawijaya1
Elok PratiwiUniversity of Brawijaya1
Fahimah FauwziyahUniversity of Brawijaya1
Ni Wayan Surya WardhaniUniversity of Brawijaya1
Loekito Adi SoehonoAfiliasi tidak diketahui1
Andi KurniawanAfiliasi tidak diketahui1
Moch. Dawam MaghfoerAfiliasi tidak diketahui1
Sisca FajrianiAfiliasi tidak diketahui1
Sudarto SudartoAfiliasi tidak diketahui1
Sri AndariniAfiliasi tidak diketahui1
Muhammad AnismuslimAfiliasi tidak diketahui1
Inayati NgoroAfiliasi tidak diketahui1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.binus.ac.id/index.php/commit/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Spatially Filtered Ridge Regression Modeling to Find Out the Rice Production Factors in East Java, Indonesia</dc:title>
	<dc:creator>Islami, Vita Dewi</dc:creator>
	<dc:creator>Fitriani, Rahma</dc:creator>
	<dc:creator>Pramoedyo, Henny</dc:creator>
	<dc:subject xml:lang="en-US">Spatially Filtered Ridge Regression</dc:subject>
	<dc:subject xml:lang="en-US">Rice Production</dc:subject>
	<dc:subject xml:lang="en-US">East Java</dc:subject>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">Bina Nusantara University</dc:publisher>
	<dc:date>2020-11-23</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.binus.ac.id/index.php/commit/article/view/6665</dc:identifier>
	<dc:identifier>10.21512/commit.v14i2.6665</dc:identifier>
	<dc:source xml:lang="en-US">CommIT (Communication and Information Technology) Journal; Vol. 14 No. 2 (2020): CommIT Journal; 95-102</dc:source>
	<dc:source>2460-7010</dc:source>
	<dc:source>1979-2484</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.binus.ac.id/index.php/commit/article/view/6665/3935</dc:relation>
	<dc:relation>10.21512/lc.v12i3.4301.s231</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2020 Vita Dewi Islami, Rahma Fitriani, Henny Pramoedyo</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>