PERAMALAN EKSPOR NONMIGAS DENGAN VARIASI KALENDER ISLAM MENGGUNAKAN X-13-ARIMA-SEATS (Studi Kasus: Ekspor Nonmigas Periode Januari 2013 sampai Desember 2017)

*Eka Lestari  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Tatik Widiharih  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Rita Rahmawati  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Published: 29 Aug 2018.
Open Access Copyright 2020 Jurnal Gaussian
License URL: http://creativecommons.org/licenses/by-nc-sa/4.0

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Abstract

Non-oil and gas exports are one of the largest foreign exchange earners for Indonesia. Non-oil and gas exports always experience a decline in the month of Eid Al-Fitr due to delays in the delivery of export goods because the loading and unloading of goods at the port is reduced during Eid Al-Fitr. The shift of the Eid Al-Fitr month on the data will form a pattern or season with an unequal period called the moving holiday effect. The time series forecasting method that usually used the ARIMA method. Because the ARIMA method only suitable for time series data with the same seasonal period and can’t handle the moving holiday effect, the X-13-ARIMA-SEATS method used two steps. First, regARIMA modeling is a linear regression between time series data and the weight of Eid Al-Fitr and the residuals follow the ARIMA process. The weighting is based on three conditions, namely pre_holiday, post_holiday, and multiple. Second, X-12-ARIMA decomposition method for seasonal adjustments that produces trend-cycle components, seasonal, and irregular. Based on the analysis carried out on the monthly non-oil and gas export data for the period January 2013 to December 2017, the X-13-ARIMA-SEATS (1,1,0) model was obtained in the post_holiday condition as the best model. The forecasting results in 2018 show the largest decline in non-oil and gas exports in June 2018 which coincided with the Eid Al-Fitr holiday. MAPE value of 10.90% is obtained which shows that the forecasting ability is good.

Keywords:  time series, non-oil and gas, X-13-ARIMA-SEATS, moving holiday

Keywords: time series, non-oil and gas, X-13-ARIMA-SEATS, moving holiday

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