TY - JOUR
T1 - Analysis of Residential Property Price Index (RPPI) Using Multi Input Transfer Function
AU - Chirsty, Y.
AU - Novita, M.
AU - Soemartojo, S. M.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2021/4/19
Y1 - 2021/4/19
N2 - Residential property or home is one of the basic human needs as a shelter, to be able to continue to live. As the population in Indonesia increases, express the need for residential property will also increase. The movement of residential property prices in Indonesia can be observed from the Residential Property Price Index (RPPI) issued by Bank Indonesia. Residential property prices can be influenced by several factors. For example in economic, the movement of RPPI can be influenced by several factors such as inflation, Composite Stock Price Index (RPPI) and loan interest rates. Forecasting the RPPI can be done with times series modeling. Modeling RPPI using three influencing variables requires a multivariate time series model. The multi-input transfer function model is a multivariate model that can be used in modeling RPPI. In the multi-input transfer function model there is an output series (y t ) which is the RPPI which is estimated to be influenced by several input series (x jt ), which are inflation, IHSG and loan interest rates. Based on the model obtained in this study, it can be seen that the prediction of RPPI at the t-time is influenced by the amount of inflation in the previous two months until previous five months, influence by loan interest rates without delay so that it is influenced by the t-time until previous three months, influenced by the IHSG at t-time until previous four months, and also influenced by itself at one month before to four months before.
AB - Residential property or home is one of the basic human needs as a shelter, to be able to continue to live. As the population in Indonesia increases, express the need for residential property will also increase. The movement of residential property prices in Indonesia can be observed from the Residential Property Price Index (RPPI) issued by Bank Indonesia. Residential property prices can be influenced by several factors. For example in economic, the movement of RPPI can be influenced by several factors such as inflation, Composite Stock Price Index (RPPI) and loan interest rates. Forecasting the RPPI can be done with times series modeling. Modeling RPPI using three influencing variables requires a multivariate time series model. The multi-input transfer function model is a multivariate model that can be used in modeling RPPI. In the multi-input transfer function model there is an output series (y t ) which is the RPPI which is estimated to be influenced by several input series (x jt ), which are inflation, IHSG and loan interest rates. Based on the model obtained in this study, it can be seen that the prediction of RPPI at the t-time is influenced by the amount of inflation in the previous two months until previous five months, influence by loan interest rates without delay so that it is influenced by the t-time until previous three months, influenced by the IHSG at t-time until previous four months, and also influenced by itself at one month before to four months before.
UR - http://www.scopus.com/inward/record.url?scp=85104806007&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1863/1/012065
DO - 10.1088/1742-6596/1863/1/012065
M3 - Conference article
AN - SCOPUS:85104806007
SN - 1742-6588
VL - 1863
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012065
T2 - International Conference on Mathematics, Statistics and Data Science 2020, ICMSDS 2020
Y2 - 11 November 2020 through 12 November 2020
ER -