Prediction of Inflation in Indonesia Using Nonparametric Regression Approach Based on Local Polynomial Estimator

DOI

10.2991/assehr.k.201010.013How to use a DOI?

Keywords

inflation, global model, local model, local polynomial estimator, MAPE

Abstract

Inflation is one of macroeconomics indicator can describe the economic development of the country. Inflation is one of the important factors, the high inflation can disturb the economy a country so it has been concerned by the government. Inflation can be caused by various factors, one of them come from the money supply. Inflation in Indonesia has a high variance so it needs a model based on high degree estimator. In this research, we predict inflation using by two approaches i.e. nonparametric (local model using local polynomial estimator) and parametric (global model). Inflation predicting can is used to prepare government policies to keep inflation at a stable. The Mean Absolute Percentage Error (MAPE) is used to know the accuracy predicted value. For nonparametric approaches, i.e. the local linear model has a MAPE as 4,933% and local quadratic model has a MAPE as 4,692%, both of them is highly accurate to predict. But, for the parametric approach (global model) has a MAPE as 29,43%. Based on MAPE, we conclude that the best model is the local quadratic model at predicting inflation.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - V Fibriyani
AU  - N Chamidah
PY  - 2020
DA  - 2020/10/11
TI  - Prediction of Inflation in Indonesia Using Nonparametric Regression Approach Based on Local Polynomial Estimator
BT  - Proceedings of the 2nd International Seminar on Science and Technology (ISSTEC 2019)
PB  - Atlantis Press
SP  - 79
EP  - 86
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201010.013
DO  - 10.2991/assehr.k.201010.013
ID  - Fibriyani2020
ER  -