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Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network

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  • N. Suhermi
  • [Unknown] Suhartono
  • R.P. Permata
  • S.P. Rahayu
Publication date30/09/2019
Host publicationSoft Computing in Data Science: 5th International Conference, SCDS 2019, Iizuka, Japan, August 28–29, 2019, Proceedings
EditorsMichael W. Berry, Bee Wah Yap, Azlinah Mohamed, Mario Koppen
Place of PublicationSingapore
Number of pages15
ISBN (electronic)9789811503993
ISBN (print)9789811503986
<mark>Original language</mark>English

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929
ISSN (electronic)1865-0937


The trend of muslim fashion has significantly raised the search trend for the brands of hijab and sarong in Indonesia. The aim of this study is to forecast the search trend for hijab and sarong based on google trends data. The Hijab brands include Rabbani, Zoya, Dian Pelangi, Elzatta, and Shafira, while the sarong brands include Gajah Duduk, Wadimor, Atlas, Mango, and Sapphire. We apply several forecasting methods such as Holt-Winters’ Exponential Smoothing, ARIMA, ARIMAX, FFNN and ERNN. The data contains calendar variation effect due to the Eid al-Fitr days use different calendar system. The results show that FFNN yields the most accurate forecast on 6 out of 10 brands. The forecast results for year 2019 period show that the search trend for Atlas brand is predicted to be the highest of all sarong brands. On the contrary, all the hijab brands’ trend search will decrease in this period.