DOI: https://doi.org/10.14710/teknik.v43i1.44234

Spatial Analysis of Urban Settlement Development in Kudus District with Cellular automata marcov Model (Case Study: Kota District, Bae District, Jati District and Kaliwungu District)

Analisis Spasial Perkembangan Kawasan Permukiman Perkotaan di Kabupaten Kudus Dengan Model Cellular Automata Marcov (Studi Kasus: Kecamatan Kota, Kecamatan Bae, Kecamatan Jati dan Kecamatan Kaliwungu)

*Fauzi Janu Amarrohman scopus  -  Departemen Teknik Geodesi, Universitas Diponegoro, Indonesia
Yasser Wahyuddin  -  Departemen Teknik Geodesi, Universitas Diponegoro, Indonesia
Elly Indah Novialis  -  Departemen Teknik Geodesi, Universitas Diponegoro, Indonesia
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Abstract
The increase in the need for residential land will encourage changes in land use functions. Monitoring the development of urban settlements in Kudus Regency, specifically in the Districts of Bae, Jati, Kaliwungu and Kota needs to be carried out so as not to cause a transfer of land use functions that deviate from the applicable RTRW. Monitoring can be done by modeling. The modeling of urban settlement development is then combined with GIS to support the spatial analysis. This study aims to determine the changes in land use function for urban settlements in 2010-2020 with the overlay identity method, apply the CA-Marcov method in predicting land use for urban settlements in 2030 and find the value of modeling conformity with the RTRW map and its development pattern using the average nearest neighbor. The data used are WordView images in 2010 and 2015, SPOT-7 images in 2020 and the RTRW Map of Kab. Holy year 2012-2032. The results showed that the development of urban settlements in 2010-2015 was 162,375 Ha, while in 2015-2020 it was 55,978 Ha. During 2010 to 2020, the food crop agricultural area changed its function into urban settlements amounting to 126,927 Ha. The area of land for urban settlements as a result of the prediction of land use in 2030 is 3323,285 Ha, where the agricultural area for food crops is the largest land converted into urban settlements of 321,803 Ha. The value of the suitability of the predicted use of 2030 with the RTRW map is 71.42%. The pattern of urban settlement development in 2030 is random.
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Keywords: landuse; modeling; settlement; RTRW; GIS

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Section: Artikel
Language : EN
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  1. Baja, S. (2012). Perencanaan tata guna lahan dalam pengembangan wilayah: pendekatan spasial dan aplikasinya. Yogyakarta: ANDI
  2. Basuki, A. Y., Oktaviani, N., & Riqqi, A. (2014). Tata Kelola Basis Data Geospasial Kelautan Berbasis Sistem Grid Skala Ragam (Wilayah Studi : Selat Sunda). Jurnal Conference on Geospatial Information Science and Engineering. 1-12
  3. Badan Informasi Geospasial. (2014). Peraturan Kepala Kepala Badan Informasi Geospasial Nomor 6 Tahun 2018 Tentang Pedoman Teknis Ketelitian Peta Dasar. Bogor: Badan Informasi Geospasial
  4. Badan Informasi Geospasial. (2016). [DRAFT] Modul Validasi Peta Rencana Tata Ruang I - VI Sumber Data Dan Peta Dasar. Bogor: Badan Informasi Geospasial
  5. Badan Informasi Geospasial. (2016). Modul Validasi Peta Rencana Tata Ruang Peta Rencana Pola Ruang. Bogor: Badan Informasi Geospasial
  6. Badan Pusat Statistik Kudus. (2020). Kabupaten Kudus dalam Angka 2020. Kudus: BPS Kudus
  7. Djufry, F., Pasandaran, E., Irawan, B., & Ariani, M. (2019). Manajemen Sumber Daya Alam dan Produksi Mendukung Pertanian Modern. Bogor: IPB Press
  8. Dewan Perwakilan Rakyat Daerah Kabupaten Kudus. (2012). Peraturan Daerah Nomor 16 Tahun 2012 tentang RTRW Kabuaten Kudus tahun 2012-2032. Kudus: DPRD Kabupaten Kudus
  9. Kubangun, S. H., Haridjaja, O. & Gandasasmita, K. (2014). Model Spasial Bahaya Lahan Kritis Di Kabupaten Bogor. PhD Thesis. Fakultas Pertanian. Institut Pertanian Bogor
  10. Mather, P. M. (1987). Computer Processing of Remotely Sensed Data: An Introduction. 3rd Ed. Chichester: Wiley
  11. Kementerian Agraria dan Tata Ruang/Badan Pertanahan Nasional. (1997). Peraturan Menteri Negara Agraria / Kepala Badan Pertanahan Nasional Nomor 3 Tahun 1997 Tentang Pedoman Teknis Peta Dasar Pendaftaran. Jakarta: BPK RI
  12. Putri, T., Sudarsono, B., & Amarrohman, F. J. (2020). Analisis Spasial Perkembangan Wilayah Kabupaten Pati Tahun 2030 Menggunakan Model Cellular Automata Markov. Jurnal Geodesi Undip. 9. 1-10
  13. Sitanala, A. (1989). Konservasi Tanah dan Air. Bogor: IPB Press
  14. Sofiyanti. (2010). Metode Agregasi Sistem Grid Emisi Gas Rumah Kaca untuk Kota Bandung. PhD Thesis. Fakultas Teknik. Institusi Teknologi Bandung
  15. Ujjwal, S. & Paramartha. (2017). Quantum Inspired Computational Intelligence. 1st Ed. California : Morgan Kaufmann
  16. Worldmeter. (2020). Indonesia Population: https://www.worldometers.info/world-population/indonesia-population/. Diakses Pada 10 November 2021
  17. Yunus, H. S. (2000). Struktur Tata Ruang Kota. Yogyakarta: Penerbit Pustaka Pelajar

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