Pengaruh Hari Raya Galungan Pada Seasonal Adjustment IHK dan Penentuan Komoditas Utama Yang Mempengaruhi Inflasi di Provinsi Bali: Analisis ARIMA

  • Putu Simpen Arini Badan Pusat Statistik Provinsi Bali
  • I Komang Gde Bendesa Jurusan Ekonomi Pembangunan Fakultas Ekonomi Universitas Udayana

Abstract

Inflation is one of macroeconomic indicators that show a rise of prices in the general level of goods and services over a period of time. The research conducted by Bank Indonesia in 2003 and 2004 show that the largest component that determine the inflation was people’s expectation. One of the required information to controling inflation expectation is the prediction of future inflation and the main commodity that make a big contribution to inflation. Consumer Price Index (CPI) data use to prediction of future inflation rate. Forecasting the time series data of CPI must be preceded with seasonal adjustment to reduce a seasonal component in time series data. Seasonal component which is tested in this study is Galungan (one of Balinese’s big ceremony). This is based on fact that the majority of Balinese are Hindust. Data which used in this research are Consumer Price Index (CPI), inflation rate, commodity price index, producer prices, and consumer prices. The method which used to seasonal adjusted is X-12 ARIMA and the method which used to forecast is SARIMA. Modus method and the principal component analysis are use to determine the main commodity which make an influence to Bali’s inflation. The results of this research are: (1) Galungan has unsignificant result as seasonal component to effect the Bali’s CPI, (2) The forecast for Bali’s inflation rate in 2012 is 6,23 percent, and (3) The main commodity that has a big contribution to influence the Bali’s inflation rate is rice.

 


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Published
2012-10-08
How to Cite
ARINI, Putu Simpen; BENDESA, I Komang Gde. Pengaruh Hari Raya Galungan Pada Seasonal Adjustment IHK dan Penentuan Komoditas Utama Yang Mempengaruhi Inflasi di Provinsi Bali: Analisis ARIMA. Jurnal Ekonomi Kuantitatif Terapan, [S.l.], oct. 2012. ISSN 2303-0186. Available at: <https://ojs.unud.ac.id/index.php/jekt/article/view/1890>. Date accessed: 12 july 2020.

Keywords

inflation ; seasonal adjustment ; forecasting ; ARIMA