Recommended Strategies Based on The Capability And Purchasing Power of Low-Income Communities (MBR) In Providing MBR Houses In Kartamantul
Abstract
The housing needs that shape urban spatial structures or the relationships between the three cannot be fully understood without considering the state of housing market prices. The reason is that changes in urban housing market prices no longer depend on the city level, but over time begin to be characterized by urban agglomeration processes. Furthermore, agglomeration dynamics that change urban spatial structure and housing market prices will have an impact on socio-economic disparities and challenges in providing affordable housing for people with low incomes in densely populated urban areas. The aim of this research is to find out whether the MBR housing allocated by the regional government is appropriately located in low-income areas/zones in KARTAMANTUL. The research methods used are web scrapping, mapping and comparative evaluation of housing locations with the distribution of MBR in KARTAMANTUL. The results obtained were to simplify the simulation of affordability and household purchasing power regarding home ownership, the researchers tried to average the income of the two categories of low-income households. Therefore, with an average MBR income limit of Rp. 3,900,000 in DIY, then the ability to repay the house in installments is IDR. 1,170,000/month. Furthermore, regarding house buildings, the criteria for a habitable house is a per capita area of at least 9 m2 per person. With the average number of family members in DIY being 4 people, the house area required per household is 36 m2. The recommendations given are a) 25 year house installments are a payment option that can be used for low-income households in KARTAMANTUL, b) the choice of house locations for MBR is mostly in Bantul Regency and Sleman Regency, both of which have urban status. fringe and urban shadow.
Keywords
Full Text:
PDFReferences
A. Nygaard, C., Parkinson, S., & Reynolds, M. (2021). Agglomeration effects and housing market dynamics. In AHURI Final Report (Issue 366). Australian Housing and Urban Research Institute Limited. https://doi.org/10.18408/ahuri5122401
Acheampong, R. A., & Asabere, S. B. (2021). Simulating the co-emergence of urban spatial structure and commute patterns in an African metropolis: A geospatial agent-based model. Habitat International, 110(March), 102343. https://doi.org/10.1016/j.habitatint.2021.102343
Afrianto, F., & Graha, D. T. R. (2023). Morfologi Kota Malang: Sebuah Tinjauan dari Nighttime Light Satellite Imagery. Plano Buana, 3(2), 68–76.
Artaningtyas, W. D., Winarti, A. S., & Sodik, J. (2019). Agglomeration and Economic Growth in the Special Region of Yogyakarta (2005-2016). Eko-Regional Jurnal Pengembangan Ekonomi Wilayah, 14(2), 75–84. https://doi.org/10.20884/1.erjpe.2019.14.2.1277
Bajracharya, B., & Hastings, P. (2018). A regional, strategic growth-management approach to urban and Peri-urban development in south east Queensland, Australia. Journal of Regional and City Planning, 29(3), 210–233. https://doi.org/10.5614/jrcp.2018.29.3.3
Brooks, M. M. (2022). Persistent disparities in affordable rental housing among America’s ethnoracial groups. Social Science Research, June, 102828. https://doi.org/10.1016/j.ssresearch.2022.102828
Bureau of Regional Infrastructure Development and Development Financing, D. R. S. (2021). Study of Monev on MBR Housing Development Policy in DIY.
Burnett, P. (2016). Land Use Regulations and Regional Economic Development. Land Economics, 92(2), 237–255. https://doi.org/10.3368/le.92.2.237
Carrión-Flores, C., & Irwin, E. G. (2004). Determinants of Residential Land-Use Conversion and Sprawl at the Rural-Urban Fringe. American Journal of Agricultural Economics, 86(4), 889–904. http://www.jstor.org/stable/4492780
Chen, M., Zhang, W., & Lu, D. (2015). Examining spatial pattern and location choice of affordable housing in Beijing, China: Developing a workable assessment framework. Urban Studies, 52(10), 1846–1863. https://doi.org/10.1177/0042098014542133
Chen, Y., Hu, Y., & Lai, L. (2022). Demography-Oriented Urban Spatial Matching of Service Facilities: Case Study of Changchun, China. Land, 11(10). https://doi.org/10.3390/land11101660
Coelho, K., Mahadevia, D., & Williams, G. (2022). Outsiders in the periphery: studies of the peripheralisation of low income housing in Ahmedabad and Chennai, India. International Journal of Housing Policy, 22(4), 543–569. https://doi.org/10.1080/19491247.2020.1785660
Devi, M. K., Gorman, Y. H., & Hidayati, S. R. (2020). Spatial transformation in urban periphery: The case of Yogyakarta. IOP Conference Series: Earth and Environmental Science, 592(1). https://doi.org/10.1088/1755-1315/592/1/012022
Equere, E., Ibem, E., & Alagbe, O. (2020). Towards city resilience: the influence of socio-cultural and economic features of housing on population growth in public residential estates. Journal of Regional and City Planning, 31(2), 164–179. https://doi.org/10.5614/jpwk.2020.31.2.4
Erdem, F., Atun, R., Yigit Avdan, Z., Atila, I., & Avdan, U. (2021). Drought analysis of Van Lake Basin with remote sensing and GIS technologies. Egyptian Journal of Remote Sensing and Space Science, 24(3), 1093–1102. https://doi.org/10.1016/j.ejrs.2021.10.006
Foelske, L., van Riper, C. J., Stewart, W., Ando, A., Gobster, P., & Hunt, L. (2019). Assessing preferences for growth on the rural-urban fringe using a stated choice analysis. Landscape and Urban Planning, 189(October 2018), 396–407. https://doi.org/10.1016/j.landurbplan.2019.05.016
Hadj Ali, C., Roy, D., Amireche, L., & Antoni, J. P. (2023). Development of a Cellular Automata-based model approach for sustainable planning of affordable housing projects: an application case study in Algiers. Land Use Policy, 125(December 2021). https://doi.org/10.1016/j.landusepol.2022.106468
Higgins, C. D. (2019). A 4D spatio-temporal approach to modelling land value uplift from rapid transit in high density and topographically-rich cities. Landscape and Urban Planning, 185(March 2018), 68–82. https://doi.org/10.1016/j.landurbplan.2018.12.011
Jansen, S. J. T. (2020). Urban, suburban or rural? Understanding preferences for the residential environment. Journal of Urbanism, 13(2), 213–235. https://doi.org/10.1080/17549175.2020.1726797
Jun, M. J. (2013). The effects of housing preference for an apartment on residential location choice in Seoul: A random bidding land use simulation approach. Land Use Policy, 35, 395–405. https://doi.org/10.1016/j.landusepol.2013.06.011
Kamim, A. B. M., Amal, I., & Khandiq, M. R. (2019). Problematika Perumahan Perkotaan di Kota Yogyakarta (Urban Housing Problems in Yogyakarta City). Jurnal Sosiologi USK (Media Pemikiran & Aplikasi), 13(1), 51. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjcsaHmjMLqAhW8_XMBHUSFDTQQFjABegQIARAB&url=http%3A%2F%2Fjurnal.unsyiah.ac.id%2FJSU%2Farticle%2Fview%2F13494&usg=AOvVaw11NdElsyFVN-OoAsoDmYd9
Li, H., Wei, Y. D., Wu, Y., & Tian, G. (2019). Analyzing housing prices in Shanghai with open data: Amenity, accessibility and urban structure. Cities, 91(October 2018), 165–179. https://doi.org/10.1016/j.cities.2018.11.016
Li, T., Shiran, S. J., & Dodson, J. (2021). Metropolitan migration and spatial housing markets: A geographical study in Melbourne. Applied Geography, 129(March), 102414. https://doi.org/10.1016/j.apgeog.2021.102414
Liu, L., Qiu, L., & Yang, Y. (2022). Urban housing prices within a core urban agglomeration in China. In SN Business & Economics (Vol. 2, Issue 11). Springer International Publishing. https://doi.org/10.1007/s43546-022-00351-x
Ma, W., Jiang, G., Zhang, R., Li, Y., & Jiang, X. (2018). Achieving rural spatial restructuring in China: A suitable framework to understand how structural transitions in rural residential land differ across peri-urban interface? Land Use Policy, 75(March), 583–593. https://doi.org/10.1016/j.landusepol.2018.04.02
DOI: http://dx.doi.org/10.31258/jip.20.1.31-39
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 JIP ( Jurnal Industri dan Perkotaan )
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.