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

Novri Suhermi; Suhartono; Regita Putri Permata; Santi Puteri Rahayu

doi:10.1007/978-981-15-0399-3_22

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

Novri Suhermi, Suhartono^*, Regita Putri Permata, Santi Puteri Rahayu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Soft Computing in Data Science - 5th International Conference, SCDS 2019, Proceedings
Editors	Michael W. Berry, Bee Wah Yap, Azlinah Mohamed, Mario Köppen
Publisher	Springer
Pages	272-286
Number of pages	15
ISBN (Print)	9789811503986
DOIs	https://doi.org/10.1007/978-981-15-0399-3_22
Publication status	Published - 2019
Event	5th International Conference on Soft Computing in Data Science, SCDS 2019 - Iizuka, Japan Duration: 28 Aug 2019 → 29 Aug 2019

Publication series

Name	Communications in Computer and Information Science
Volume	1100
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	5th International Conference on Soft Computing in Data Science, SCDS 2019
Country/Territory	Japan
City	Iizuka
Period	28/08/19 → 29/08/19

Keywords

ARIMA
ARIMAX
ERNN
FFNN
Forecasting
Google trends

Access to Document

10.1007/978-981-15-0399-3_22

Cite this

Suhermi, N., Suhartono, Permata, R. P., & Rahayu, S. P. (2019). Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network. In M. W. Berry, B. W. Yap, A. Mohamed, & M. Köppen (Eds.), Soft Computing in Data Science - 5th International Conference, SCDS 2019, Proceedings (pp. 272-286). (Communications in Computer and Information Science; Vol. 1100). Springer. https://doi.org/10.1007/978-981-15-0399-3_22

Suhermi, Novri ; Suhartono ; Permata, Regita Putri et al. / Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network. Soft Computing in Data Science - 5th International Conference, SCDS 2019, Proceedings. editor / Michael W. Berry ; Bee Wah Yap ; Azlinah Mohamed ; Mario Köppen. Springer, 2019. pp. 272-286 (Communications in Computer and Information Science).

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

abstract = "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{\textquoteright} 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{\textquoteright} trend search will decrease in this period.",

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author = "Novri Suhermi and Suhartono and Permata, {Regita Putri} and Rahayu, {Santi Puteri}",

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Suhermi, N, Suhartono, Permata, RP & Rahayu, SP 2019, Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network. in MW Berry, BW Yap, A Mohamed & M Köppen (eds), Soft Computing in Data Science - 5th International Conference, SCDS 2019, Proceedings. Communications in Computer and Information Science, vol. 1100, Springer, pp. 272-286, 5th International Conference on Soft Computing in Data Science, SCDS 2019, Iizuka, Japan, 28/08/19. https://doi.org/10.1007/978-981-15-0399-3_22

Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network. / Suhermi, Novri; Suhartono; Permata, Regita Putri et al.
Soft Computing in Data Science - 5th International Conference, SCDS 2019, Proceedings. ed. / Michael W. Berry; Bee Wah Yap; Azlinah Mohamed; Mario Köppen. Springer, 2019. p. 272-286 (Communications in Computer and Information Science; Vol. 1100).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Y2 - 28 August 2019 through 29 August 2019

ER -

Suhermi N, Suhartono, Permata RP, Rahayu SP. Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network. In Berry MW, Yap BW, Mohamed A, Köppen M, editors, Soft Computing in Data Science - 5th International Conference, SCDS 2019, Proceedings. Springer. 2019. p. 272-286. (Communications in Computer and Information Science). doi: 10.1007/978-981-15-0399-3_22

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

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Keywords

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