Modeling And Spatial Analysis Of Change Settlement And Fair Market Land Price Using Markov Chain Model In Banyumanik District
Banyumanik District is located on the outskirts of Semarang with very rapid development. Indicated with the many changes in land that occur, due to the construction of settlements and other physical buildings continues to increase. Changes in land use will also be followed by changes in market land prices. These changes will continue in line with the increasing number and activities of the population in carrying out economic, social and cultural life. Most of the studies was conducted to analyze changes in future land use are based on the use of a model. Land use modeling changes is a method or approach that can be used to understand the causes and effects of these dynamic changes. The Multi-Layer Perceptron (MLP) Neural Network and Markov Chain methods are used in this study to determine which locations or areas of land use are vacant land and agriculture has the potential to change into settlements and test the predictive ability that will be produced by the model. The driving factor for land use change as an input model consists of distance to the road, distance to the area experiencing changes in land use, slope, elevation and fair market land prices. This study aims to (1) predict settlement and its changes in Banyumanik District using High Resolution Satellite Image in 2011-2019, (2) build a model of settlement land use change with the Markov Chain methods and (3) projection of Banyumanik District land use in 2028.
 S, Subiyanto and L, Fadilla. (2018). Monitoring land use change and urban sprawl based on spatial structure to prioritize specific regulations in Semarang, Indonesia in IOP Conf. Ser.: Earth Environ. Sci. IOP Publishing.
 S, Subiyanto and Amarrohman, F. J. (2017). Vacant Land Availability and Land Value Factor for Determining Directions of Regional Development in Banyumanik District Period 2011, 2013, and 2016, in The 8th Rural Research And Planning Group International Conference. Yogyakarta: Geography Departement, Faculty of Geography, Gadjah Mada University.
 S, Subiyanto. (2018). Analysis of Changes in Vacant Land and Fair Market Land Prices to Determine Direction of Settlement Development in Tembalang District Period 2010 and 2016 in IOP Conf. Ser.: Earth Environ. Sci. IOP Publishing.
 Lambin, E. F., et al. (2000). Are Current Agricultural Land Use Models Able to Predict Changes in Land Use Intensity?. Agriculture, Ecosystems and Environment, vol. 1653, pp. 1–11.
 Veldkamp, A. and Lambin, E. F. (2001). Editorial: Predicting Land Use Change. Agriculture, Ecosystems and Environment, vol. 85, pp. 1–6.
 Veldkamp, A. and Fresco, L. O. (1995). CLUE-CR: An Integrated Multi-scale Model to Simulate Land Use Change Scenarios in Costa Rica. Ecological Modelling, vol. 91, pp. 231–248.
 Wijaya, C. I. (2011). Land Use Change Modelling In Siak District, Riau Province, Indonesia Using Multinomial Logistic Regression. Tesis. Sekolah Pascasarjana Institut Pertanian Bogor.
 Wu, Q. et al. (2006). Monitoring and Predicting Land Use Change in Beijing Using Remote Sensing. Landscape and Urban Planning, vol. 78, pp. 322–333.
 Berger, T., et al. (2001). Introduction and conceptual overview, in Report and review of International Workshop October 4-7. California USA.
 Batty, M. and Longley, P. A. (1994). Urban Modelling in Computer Graphic and Geographic Information System Environments. Environment and Planning, vol. 19, pp. 663–688.
 Bockstael, N. et al. (1995). Ecological Economic Modelling and Valuation of Ecosystems. Ecological Economics, vol. 14, pp. 143–159.
 Luo, J. (2004). Modelling Urban Land Value in GIS Environment.
 Wijaya, M. S., & Umam, N. (2015). Pemodelan Spasial Perkembangan Fisik Perkotaan Yogyakarta Menggunakan Model Cellular Automata dan Regresi Logistik Biner. Majalah Ilmiah Globë, 17(2), 165–172.