I Gusti Bagus Ngurah Diksa
Badan Pusat Statistik Provinsi Sulawesi Selatan, INDONESIA

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Peramalan Eksistensi Cokelat dengan Efek Calender Variation dan Seasonal Menggunakan Pendekatan Time Series Klasik I Gusti Bagus Ngurah Diksa
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 2 (2022): JANUARY 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i2.18542

Abstract

Chocolate is the raw material for making cakes, so consumption of chocolate also increases on Eid al-Fitr. However, this is different in the United States where the tradition of sharing chocolate cake is carried out on Christmas. To monitor the existence of this chocolate can be through the movement of data on Google Trends. This study aims to predict the existence of chocolate from the Google trend where the use of chocolate by the community fluctuates according to the calendar variance and seasonal rhythm. The method used is classic time series, namely nave, double exponential smoothing, multiplicative decomposition, addictive decomposition, holt winter multiplicative, holt winter addictive, time series regression, hybrid time series, ARIMA, and ARIMAX. Based on MAPE in sample, the best time series model to model the existence of chocolate in Indonesia is ARIMAX (1,0,0) while for the United States it is Hybrid Time Series Regression-ARIMA(2,1,[10]). For forecasting the existence of chocolate in Indonesia, the best models in forecasting are ARIMA (([11],[12]),1,1) and Naïve Seasonal. In contrast to the best forecasting model for the existence of chocolate in the United States, namely Hybrid Naïve Seasonal-SARIMA (2,1,0)(0,0,1)12 Hybrid Time Series Regression- ARIMA(2,1,[10]), Time Series Regression, Winter Multiplicative, ARIMAX([3],0,0).