Among the key challenges, the construction industry sector faces are matching the supply of and demand for affordable housing. It is very crucial to predict low-cost housing demand to match the demand and supply so that the government can plan the allocation of low-cost housing based on the demand. In Johor, housing provision is very crucial due to urbanization. The supply of houses seems to be swamping the demand for luxury condos and houses, especially in Johor Bharu. Time series data on low-cost housing demand have been converted to Ln before developing the model. The actual data and forecasted data will be compared and validated using Mean Absolute Percentage Error (MAPE). After that, the results using the ARIMA method will be compared with the ANN method. The results show that MAPE analysis for ARIMA is 15.39% while ANN is 18.27%. It can be concluded that the ARIMA model can forecast low-cost housing demand in Johor quite good.