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PENGGUNAAN CITRA QUICKBIRD UNTUK MENGIDENTIFIKASI KEMACETAN LALU LINTAS DI KOTA SEMARANG BERDASARKAN POLA JARINGAN JALAN

Geo-Image Journal · Vol. 1 No. 1 (2012)

DOI
10.15294/geoimage.v1i1.948
ISSN
2549-0362, 2252-6285
Published
2012-06-29
Publisher
Universitas Negeri Semarang
Language
eng

Abstract

Pertambahan penduduk mendorong perubahan tak terbatas pada jumlah penduduk, Penelitian ABSTRAKKemacetan adalah situasi atau keadaan tersendatnya atau bahkan terhentinya lalu lintas yang disebabkan oleh banyaknya jumlah kendaraan yang melebihi kapasitas jalan. Banyak dijumpai kemacetan lalu lintas di beberapa titik yang terdapat di Kota Semarang. Permasalahan yang akan dikaji dalam penelitian ini adalah, (1) Ketepatan Citra Satelit Quickbird untuk identifikasi kemacetan lalu lintas di Kota Semarang. (2) Karakteristik titik-titik rawan kemacetan di Kota Semarang. (3) Pola jalan pada daerah rawan kemacetan lalu lintas di Kota Semarang dengan menggunakan Citra Satelit QuickBird. Tujuan penelitian ini adalah: (1) Mengetahui sejauh mana tingkat ketepatan Citra Quickbird untuk identifikasi kemacetan lalu lintas di Kota Semarang. (2) Mengetahui karakteristik titik-titik rawan kemacetan di Kota Semarang. (3) Mengetahui pola jalan pada daerah rawan kemacetan lalu lintas di Kota Semarang. Populasi dalam penelitian ini adalah jaringan jalan yang rawan kemacetan di Kota Semarang. Sampel dalam penelitian ini adalah jumlah titik rawan kemacetan lalu lintas diihat menggunakan Citra Satelit QuickBird yaitu sebanyak 19 titik kemacetan. Variabel dalam penelitian ini panjang dan lebar jalan, Pola jaringan jalan, Landuse, dan Kecepatan rata-rata arus lalu lintas. Metode pengumpulan data yang digunakan adalah metode dokumentasi dan metode survei. Teknik analisis data yang digunakan dalam skripsi ini adalah (1) Analisis deskriptif, (2) Analisis Kuantitatif.Hasil skripsi ini adalah ketepatan Citra Satelit QuickBird untuk identifikasi kemacetan lalu lintas di Kota Semarang 86 %. Setelah menentukan titik kemacetan yang ada di Citra Satelit QuickBird, kemudian cek lapangan dan memperoleh 19 titik kemacetan, dan membandingkan data dari Dinas Bina Marga dengan perhitungan menggunakan Citra Satelit. Karakteristik titik-titik rawan kemacetan di Kota Semarang berbeda-beda, diantaranya dipengaruhi oleh penggunaan lahan di sekitarnya. Penggunaan lahan disekitar titik rawan bencana diantaranya terdapat kawasan perkantoran, jalan keluar/masuk tol, adanya aktivitas pendidikan, dan aktivitas pasar. Pola jaringan jalan titik-titik kemacetan di Kota Semarang adalah Grid Network, Radial Network, Linier Network, dan Modified Radial Network. Titik kemacetan di Kota Semarang sebagian besar memiliki pola jaringan jalan Radial Network, yaitu pola jalan yang menuju satu titik pusat yang menghubungkan ke beberapa jalan lainnya.Congestion is a situation or circumstance stagnated or even interruption of the traffic caused by the large number of vehicles that exceed the capacity of the road. Encountered a traffic jam at some point contained in Semarang. Issues that will be examined in this study were (1) the accuracy of Quickbird Satellite Imagery for the identification of traffic congestion in the city of Semarang. (2) Characteristics prone congestion points in the city of Semarang. (3) The pattern of roads in areas prone to traffic jams in the city of Semarang by using QuickBird satellite imagery. The purpose of this study were: (1) the extent to which the level of accuracy of Quickbird images for the identification of traffic congestion in the city of Semarang. (2) Knowing the characteristics of the vulnerable points of congestion in the city of Semarang. (3) Knowing the pattern of roads in areas prone to traffic jams in the city of Semarang. The population is prone to road network congestion in the city of Semarang. The sample in this study was the amount of traffic congestion blackspots viewed using QuickBird Satellite Imagery as many as 19 points congestion. The variables in this study the length and width of the road, the road network pattern, Landuse, and the average speed of traffic flow. Data collection methods were used: documentation method and survey method. Data analysis techniques used in this paper are (1) a descriptive analysis, (2) Quantitative Analysis.The results of this final project is the accuracy of QuickBird satellite imagery to identify traffic jams in the city of Semarang 86%. After determining the point of congestion existing QuickBird satellite imagery, then check the field and earn 19 points congestion, and compare data from the Department of Highways with calculations using satellite imagery. Characteristic points of traffic jam in the city of Semarang is different, of which is influenced by the surrounding land use. The use of land around the point there is a region prone to disasters such as office buildings, the exit / entry tolls, the educational activity, and market activity. The pattern of road network congestion points in the city of Semarang is a Grid Network, Radial Network, Linear Network, and Modified Radial Network. Congestion points in the city of Semarang mostly have patterns of road networks Radial Network, which is the pattern that led to one central point that connects to several other roads.

Collaboration network of the authors

40 authors · 176 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
  • University of Brawijaya
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Puji HardatiAffiliation unknown9
Sriyono SriyonoAffiliation unknown9
Erni SuhariniAffiliation unknown7
Andi Irwan BenardiAffiliation unknown7
Eva BanowatiAffiliation unknown5
Dewi Liesnoor SetyowatiState University of Semarang4
Ananto AjiAffiliation unknown4
SriyantoAffiliation unknown3
Tukidi TukidiAffiliation unknown3
Sriyanto SriyantoAffiliation unknown2
Wahyu SetyaningsihAffiliation unknown2
Suroso SurosoAffiliation unknown2
Apik Budi SantosoAffiliation unknown2
Muh. SholehAffiliation unknown2
Juhadi JuhadiAffiliation unknown2
Moch. ArifienAffiliation unknown2
Ariyani IndrayatiAffiliation unknown2
Satya Budi NugrahaAffiliation unknown2
Rahma HayatiAffiliation unknown2
Salahuddin SalahuddinUniversitas Gadjah Mada1
Nurhayu MalikAffiliation unknown1
Viera WardhaniUniversity of Brawijaya1
Siswanto SiswantoAffiliation unknown1
Supriyadi SupriyadiAffiliation unknown1
Ervando Tommy Al-hanifAffiliation unknown1
Mohammad SyifauddinAffiliation unknown1
Deby Luriawati NaryatmojoAffiliation unknown1
Andri Sumihar SimbolonAffiliation unknown1
Herlambang Fadlan SejatiAffiliation unknown1
Puneet IyerAffiliation unknown1
Nur FauziyahAffiliation unknown1
Afkar Jihad Al-afghani AfkarAffiliation unknown1
Andina Ahya PrameswariAffiliation unknown1
Bella Zulfia Aisyatul WahidahAffiliation unknown1
Tjaturahono Budi SanjotoAffiliation unknown1
Dwi JatmikoAffiliation unknown1
Novia Retno NingsihAffiliation 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">PENGGUNAAN CITRA QUICKBIRD UNTUK MENGIDENTIFIKASI KEMACETAN LALU LINTAS DI KOTA SEMARANG BERDASARKAN POLA JARINGAN JALAN</dc:title>
	<dc:creator>Monica, Devy</dc:creator>
	<dc:creator>Hariyanto, Hariyanto</dc:creator>
	<dc:creator>Putro, Saptono</dc:creator>
	<dc:description xml:lang="en-US">Pertambahan penduduk mendorong perubahan tak terbatas pada jumlah penduduk, Penelitian ABSTRAKKemacetan adalah situasi atau keadaan tersendatnya atau bahkan terhentinya lalu lintas yang disebabkan oleh banyaknya jumlah kendaraan yang melebihi kapasitas jalan. Banyak dijumpai kemacetan lalu lintas di beberapa titik yang terdapat di Kota Semarang . Permasalahan yang akan dikaji dalam penelitian ini adalah, (1) Ketepatan Citra Satelit Quickbird untuk identifikasi kemacetan lalu lintas di Kota Semarang. (2) Karakteristik titik-titik rawan kemacetan di Kota Semarang. (3) Pola jalan pada daerah rawan kemacetan lalu lintas di Kota Semarang dengan menggunakan Citra Satelit QuickBird. Tujuan penelitian ini adalah: (1) Mengetahui sejauh mana tingkat ketepatan Citra Quickbird untuk identifikasi kemacetan lalu lintas di Kota Semarang. (2) Mengetahui karakteristik titik-titik rawan kemacetan di Kota Semarang. (3) Mengetahui pola jalan pada daerah rawan kemacetan lalu lintas di Kota Semarang. Populasi dalam penelitian ini adalah jaringan jalan yang rawan kemacetan di Kota Semarang.  Sampel dalam penelitian ini adalah jumlah titik rawan kemacetan lalu lintas diihat menggunakan Citra Satelit QuickBird yaitu sebanyak 19 titik kemacetan. Variabel dalam penelitian ini panjang dan lebar jalan, Pola jaringan jalan, Landuse, dan Kecepatan rata-rata arus lalu lintas. Metode pengumpulan data yang digunakan adalah metode dokumentasi dan metode survei. Teknik analisis data yang digunakan dalam skripsi ini adalah (1) Analisis deskriptif, (2) Analisis Kuantitatif.Hasil skripsi ini adalah ketepatan Citra Satelit QuickBird untuk identifikasi kemacetan lalu lintas di Kota Semarang 86 %. Setelah menentukan titik kemacetan yang ada di Citra Satelit QuickBird, kemudian cek lapangan dan memperoleh 19 titik kemacetan, dan membandingkan data dari Dinas Bina Marga dengan perhitungan menggunakan Citra Satelit. Karakteristik titik-titik rawan kemacetan di Kota Semarang berbeda-beda, diantaranya dipengaruhi oleh penggunaan lahan di sekitarnya. Penggunaan lahan disekitar titik rawan bencana diantaranya terdapat kawasan perkantoran, jalan keluar/masuk tol, adanya aktivitas pendidikan, dan aktivitas pasar. Pola jaringan jalan titik-titik kemacetan di Kota Semarang adalah Grid Network, Radial Network, Linier Network, dan Modified Radial Network. Titik kemacetan di Kota Semarang sebagian besar memiliki pola jaringan jalan Radial Network, yaitu pola jalan yang menuju satu titik pusat yang menghubungkan ke beberapa jalan lainnya.Congestion is a situation or circumstance stagnated or even interruption of the traffic caused by the large number of vehicles that exceed the capacity of the road. Encountered a traffic jam at some point contained in Semarang. Issues that will be examined in this study were (1) the accuracy of Quickbird Satellite Imagery for the identification of traffic congestion in the city of Semarang. (2) Characteristics prone congestion points in the city of Semarang. (3) The pattern of roads in areas prone to traffic jams in the city of Semarang by using QuickBird satellite imagery. The purpose of this study were: (1) the extent to which the level of accuracy of Quickbird images for the identification of traffic congestion in the city of Semarang. (2) Knowing the characteristics of the vulnerable points of congestion in the city of Semarang. (3) Knowing the pattern of roads in areas prone to traffic jams in the city of Semarang. The population is prone to road network congestion in the city of Semarang. The sample in this study was the amount of traffic congestion blackspots viewed using QuickBird Satellite Imagery as many as 19 points congestion. The variables in this study the length and width of the road, the road network pattern, Landuse, and the average speed of traffic flow. Data collection methods were used: documentation method and survey method. Data analysis techniques used in this paper are (1) a descriptive analysis, (2) Quantitative Analysis.The results of this final project is the accuracy of QuickBird satellite imagery to identify traffic jams in the city of Semarang 86%. After determining the point of congestion existing QuickBird satellite imagery, then check the field and earn 19 points congestion, and compare data from the Department of Highways with calculations using satellite imagery. Characteristic points of traffic jam in the city of Semarang is different, of which is influenced by the surrounding land use. The use of land around the point there is a region prone to disasters such as office buildings, the exit / entry tolls, the educational activity, and market activity. The pattern of road network congestion points in the city of Semarang is a Grid Network, Radial Network, Linear Network, and Modified Radial Network. Congestion points in the city of Semarang mostly have patterns of road networks Radial Network, which is the pattern that led to one central point that connects to several other roads.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2012-06-29</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<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/948</dc:identifier>
	<dc:identifier>10.15294/geoimage.v1i1.948</dc:identifier>
	<dc:source xml:lang="en-US">Geo-Image Journal; Vol 1 No 1 (2012)</dc:source>
	<dc:source>2549-0362</dc:source>
	<dc:source>2252-6285</dc:source>
	<dc:source>10.15294/geoimage.v1i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/geoimage/article/view/948/976</dc:relation>
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