Forecasting Electricity Consumption Based on Economics and Social Indicators Using Var Model with Exogenous Variable: Evidence from East Java Province

Imaduddin Farih, Dedy Dwi Prastyo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Economic conditions are very important to get attention. Economic growth is one indicator of community welfare in a region. Indonesia is an archipelagic country with 34 provinces, where each province has different social, cultural, and geographical conditions, so country-level economic conditions have not been able to fully describe the economic conditions in each region. This research was conducted to meet the need for a more specific analysis about the relationship between several regional economic indicators. One of the region's economic indicators is Gross Regional Domestic Income (GRDP). In addition, other factors are considered to affect economic indicators, such as the total population in the area and electrical consumption. It needs to be analyzed to obtain knowledge regarding the relationship between these variables. Time series data used as material analysis taken from 1991 to 2021. In this study, multivariate time series analysis was used with the Vector Autoregressive (VAR) model through several testing stages such as stationarity, cointegration, residual, causality, and others to obtain the form of optimal models. From the analysis process that has been carried out, the results show that the growth of electricity consumption influences the growth of GRDP but not vice versa (unidirectional causality). This shows that policies related to the availability of electrical energy and the use of electrical energy will be able to have a positive influence on GRDP growth. In this study, the forecasting process was also carried out based on the obtained model. So we have the prediction value for electricity consumption given the predicted GRDP available for the next few years, which can be used in planning strategies or policies for the Government and related parties.

Original languageEnglish
Title of host publicationProceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering
Subtitle of host publicationApplying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages373-378
Number of pages6
ISBN (Electronic)9798350399615
DOIs
Publication statusPublished - 2022
Event6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022 - Virtual, Online, Indonesia
Duration: 13 Dec 202214 Dec 2022

Publication series

NameProceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022

Conference

Conference6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022
Country/TerritoryIndonesia
CityVirtual, Online
Period13/12/2214/12/22

Keywords

  • Macroeconomic
  • Multivariate Time series
  • Vector Autoregression

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