Main Article Content

Anak Agung Gde Satia Utama


The purpose of this study is to provide the best model and provide information on what factors affect the selling price of a house in two major cities in Indonesia, namely Surabaya and Denpasar. This study uses web-based survey data on one of the largest home sales sites in Indonesia. The data obtained were 110 houses and processed using Minitab software. Data analysis uses regression. The results obtained indicate that there are differences in factors that affect the selling price of houses in the two cities. The electric power factor (kilowatt hour) and land area (LSF) are both factors that affect housing prices in both cities. The contribution of this research can be additional information for consumers, developers, or property investors in the activity of demand transactions and offers for home sales.

Article Details

How to Cite
Anak Agung Gde Satia Utama. (2022). THE BEST MODEL AND VARIABLES AFFECTING HOUSING VALUES OF BIG CITIES IN INDONESIA. Galaxy International Interdisciplinary Research Journal, 10(6), 782–793. Retrieved from


Al-Masum, M. A., & Lee, C. L. (2019). Modeling housing prices and market fundamentals: evidence from the Sydney housing market. International Journal of Housing Markets and Analysis, 12(4), 746–762.

Chang, Y., Cutts, A. C., & Green, R. K. (2005). Did Changing Rents Explain Changing House Prices During the 1990s? Unpublished Manuscript. George Washington University, (April).

Chang, Y. F., Choong, W. C., Looi, S. Y., Pan, W. Y., & Goh, H. L. (2019). Analysis of housing prices in Petaling district, Malaysia using functional relationship model. International Journal of Housing Markets and Analysis, 12(5), 884–905.

de Vries, P. (2010). Measuring and explaining house price developments. Sustainable urban areas; 36.

Engle, R. F., Lilien, D. M., & Watson, M. (1985). A dynamic model of housing price determination. Journal of Econometrics, 28(3), 307–326.

Galati, G., & Teppa, F. (2017). Heterogeneity in House Price Dynamics. SSRN Electronic Journal.

Ge, J. (2017). Endogenous rise and collapse of housing price: An agent-based model of the housing market. Computers, Environment and Urban Systems, 62, 182–198.

Hilbers, P., Hoffmaister, A. W., Banerji, A., & Shi, H. (2008). House Price Developments in Europe : A Comparison. International Monetary Fund.

Meen, G. (2012). Price determination in housing markets. In International Encyclopedia of Housing and Home (pp. 352–360).

Nur, A., Ema, R., Taufiq, H., & Firdaus, W. (2017). Modeling House Price Prediction using Regression Analysis and Particle Swarm Optimization Case Study : Malang, East Java, Indonesia. International Journal of Advanced Computer Science and Applications, 8(10).

Oh, K., & Lee, W. (2002). Estimating the value of landscape visibility in apartment housing prices. Journal of Architectural and Planning Research, 19(1), 1–11.

Ozgur, C., Ph, D., Hughes, Z., Rogers, G., & Parveen, S. (2016). Multiple Linear Regression Applications in Real Estate Pricing, 4(8).

Sandbhor, S. S., & Chaphalkar, N. B. (2016). State of the art report on variables affecting housing value. Indian Journal of Science and Technology, 9(17).

Yusof, A., & Ismail, S. (2012). Multiple Regressions in Analysing House Price Variations. Communications of the IBIMA, 2012, 1–9.