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Pengaruh Rob Terhadap Perubahan Pendapatan Petani Tambak di Kecamatan Tirto Kabupaten Pekalongan

Geo-Image Journal · Vol. 8 No. 1 (2019) · pp. 15–21

DOI
10.15294/geoimage.v8i1.29661
ISSN
2549-0362, 2252-6285
Published
2019-04-04
Publisher
Universitas Negeri Semarang
Language
eng

Abstract

This study aims: To find out the tidal flood conditions by using a Geographic Information System. (2) Knowing the effect of tidal floods on population income. (3) Knowing adaptation strategies for rob floods. This study uses descriptive quantitative research methods with simple linear regression statistical analysis techniques. The results showed that the results showed that all villages in the northern part of the Tirto sub-district were affected by the tidal floods. The results of linear regression analysis between tidal flood heights and farmer farmer income showed a correlation value (R) of 0.32 and a coefficient of determination (R2) of 0.10 which means that both variables have a low relationship and influence. The adaptation strategy of the farmer to the tidal flood is that the community makes improvements to the pond land by means of waring, making retaining embankments and planting mangroves. The suggestion from this research is that the parameters used to determine the tidal flood area should be more complete. In addition, the development of similar studies to determine the effect of tidal flood heights with farmer farmer income must consider the ownership factors, the location of the ponds of each farmer and the productivity of the farm.

Collaboration network of the authors

40 authors · 109 co-authorship links · showing the 40 most connected

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • State University of Semarang
  • Universitas Gadjah Mada
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Erni SuhariniAffiliation unknown7
Eva BanowatiAffiliation unknown5
Saptono PutroAffiliation unknown5
Dewi Liesnoor SetyowatiState University of Semarang4
Sriyono SriyonoAffiliation unknown4
Puji HardatiAffiliation unknown3
Ananto AjiAffiliation unknown2
Suroso SurosoAffiliation unknown2
Andi Irwan BenardiAffiliation unknown2
Salahuddin SalahuddinUniversitas Gadjah Mada1
Nurhayu MalikAffiliation unknown1
Supriyadi SupriyadiAffiliation unknown1
Ervando Tommy Al-hanifAffiliation unknown1
Mohammad SyifauddinAffiliation unknown1
Herlambang Fadlan SejatiAffiliation unknown1
Puneet IyerAffiliation unknown1
Juhadi JuhadiAffiliation unknown1
Afkar Jihad Al-afghani AfkarAffiliation unknown1
Muh. SholehAffiliation unknown1
Bella Zulfia Aisyatul WahidahAffiliation unknown1
R SugiyantoAffiliation unknown1
tahmid fitriantoAffiliation unknown1
Agus ArifinAffiliation unknown1
Tukidi TukidiAffiliation unknown1
Moch. ArifienAffiliation unknown1
Fajar RianawatiAffiliation unknown1
Nurdianto NurdiantoAffiliation unknown1
Dewi Liesnoor SetyawatiAffiliation unknown1
Sudharmono SudharmonoAffiliation unknown1
Dedy Hendra PrastiaAffiliation unknown1
Mas Aditia NugrohoAffiliation unknown1
Ganes NalisaAffiliation unknown1
Eldo Rado SilabanAffiliation unknown1
Inka Wahyu SafitriAffiliation unknown1
Irna Nur Fita SariAffiliation unknown1
Arinta Yuni AstantiAffiliation unknown1
Mila WardaniAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/geoimage/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">Pengaruh Rob Terhadap Perubahan Pendapatan Petani Tambak di Kecamatan Tirto Kabupaten Pekalongan</dc:title>
	<dc:creator>Febrian, Ramadhan</dc:creator>
	<dc:creator>Eva, Banowati</dc:creator>
	<dc:creator>Hariyanto, Hariyanto</dc:creator>
	<dc:description xml:lang="en-US">This study aims: To find out the tidal flood conditions by using a Geographic Information System. (2) Knowing the effect of tidal floods on population income. (3) Knowing adaptation strategies for rob floods. This study uses descriptive quantitative research methods with simple linear regression statistical analysis techniques. The results showed that the results showed that all villages in the northern part of the Tirto sub-district were affected by the tidal floods. The results of linear regression analysis between tidal flood heights and farmer farmer income showed a correlation value (R) of 0.32 and a coefficient of determination (R2) of 0.10 which means that both variables have a low relationship and influence. The adaptation strategy of the farmer to the tidal flood is that the community makes improvements to the pond land by means of waring, making retaining embankments and planting mangroves. The suggestion from this research is that the parameters used to determine the tidal flood area should be more complete. In addition, the development of similar studies to determine the effect of tidal flood heights with farmer farmer income must consider the ownership factors, the location of the ponds of each farmer and the productivity of the farm.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2019-04-04</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.unnes.ac.id/sju/geoimage/article/view/29661</dc:identifier>
	<dc:identifier>10.15294/geoimage.v8i1.29661</dc:identifier>
	<dc:source xml:lang="en-US">Geo-Image Journal; Vol 8 No 1 (2019): Geo-Image; 15 - 21</dc:source>
	<dc:source>2549-0362</dc:source>
	<dc:source>2252-6285</dc:source>
	<dc:source>10.15294/geoimage.v8i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/geoimage/article/view/29661/13053</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2019 Geo-Image</dc:rights>
	<dc:rights xml:lang="en-US">https://journal.unnes.ac.id/sju/index.php/geoimage</dc:rights>
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