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PERAMALAN HARGA GULA PASIR MENGGUNAKAN VARIASI KALENDER REGARIMA DENGAN MOVING HOLIDAY EFFECT (PERIODE JANUARI 2018 SAMPAI DENGAN DESEMBER 2022 DI PASAR KOTA SEMARANG) | Pallupi | Jurnal Gaussian skip to main content

PERAMALAN HARGA GULA PASIR MENGGUNAKAN VARIASI KALENDER REGARIMA DENGAN MOVING HOLIDAY EFFECT (PERIODE JANUARI 2018 SAMPAI DENGAN DESEMBER 2022 DI PASAR KOTA SEMARANG)

*Diah Ayu Pallupi  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Tarno Tarno  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
agus rusgiyono  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
National sugar production is decreasing day by day with the pattern of people's consumption of sugar continuing to increase, thus encouraging the government to import sugar from other countries to meet food needs. This is because the import of granulated sugar causes the price of local granulated sugar to fluctuate which can rise up to 2 times the highest retail price. Eid al-Fitr is determined based on the Islamic calendar, this will cause a shift in the date each year on the Maseh calendar, the date of the celebration of Eid al-Fitr which moves from year to year is known as the "moving holiday effect". One of the calendar variation models used to eliminate the Holiday Effect Transfer and has a simple processing flow is the RegARIMA model. The RegARIMA model method is a modeling technique that combines the ARIMA model with the regression model. In the regression model, the weight matrix is used as the independent variable and the price of granulated sugar is used as the dependent variable. The weight value is obtained based on the number of days that affect Eid, which is 14 days. Based on an analysis of the price of granulated sugar in the Semarang City market for the period January 2018 to December 2022, the best model is obtained, namely SARIMA (1,0,0)12 with the smallest AIC value and the sMAPE value obtained from forecasting data for 2021 is of 19.04%, which means that the forecasting is still at a reasonable level.

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Keywords: RegARIMA, Moving Holiday Effect, Peramalan, Nilai Pembobot

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