Standard
Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network. /
Suhermi, N.; Suhartono, [Unknown]; Permata, R.P. et al.
Soft Computing in Data Science: 5th International Conference, SCDS 2019, Iizuka, Japan, August 28–29, 2019, Proceedings. ed. / Michael W. Berry; Bee Wah Yap; Azlinah Mohamed; Mario Koppen. Singapore: Springer, 2019. p. 272-286 (Communications in Computer and Information Science; Vol. 1100).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Suhermi, N, Suhartono, U, 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 Koppen (eds),
Soft Computing in Data Science: 5th International Conference, SCDS 2019, Iizuka, Japan, August 28–29, 2019, Proceedings. Communications in Computer and Information Science, vol. 1100, Springer, Singapore, pp. 272-286.
https://doi.org/10.1007/978-981-15-0399-3_22
APA
Suhermi, N., Suhartono, U., 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. Koppen (Eds.),
Soft Computing in Data Science: 5th International Conference, SCDS 2019, Iizuka, Japan, August 28–29, 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
Vancouver
Suhermi N, Suhartono U, 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, Koppen M, editors, Soft Computing in Data Science: 5th International Conference, SCDS 2019, Iizuka, Japan, August 28–29, 2019, Proceedings. Singapore: Springer. 2019. p. 272-286. (Communications in Computer and Information Science). Epub 2019 Sept 24. doi: 10.1007/978-981-15-0399-3_22
Author
Suhermi, N. ; Suhartono, [Unknown] ; Permata, R.P. 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, Iizuka, Japan, August 28–29, 2019, Proceedings. editor / Michael W. Berry ; Bee Wah Yap ; Azlinah Mohamed ; Mario Koppen. Singapore : Springer, 2019. pp. 272-286 (Communications in Computer and Information Science).
Bibtex
@inproceedings{027736dc8cf84a3f9b32a1d1ad5c729f,
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.",
keywords = "ARIMA, ARIMAX, ERNN, FFNN, Forecasting, Google trends",
author = "N. Suhermi and [Unknown] Suhartono and R.P. Permata and S.P. Rahayu",
year = "2019",
month = sep,
day = "30",
doi = "10.1007/978-981-15-0399-3_22",
language = "English",
isbn = "9789811503986",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "272--286",
editor = "Berry, {Michael W.} and Yap, {Bee Wah} and Azlinah Mohamed and Mario Koppen",
booktitle = "Soft Computing in Data Science",
}
RIS
TY - GEN
T1 - Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network
AU - Suhermi, N.
AU - Suhartono, [Unknown]
AU - Permata, R.P.
AU - Rahayu, S.P.
PY - 2019/9/30
Y1 - 2019/9/30
N2 - 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.
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.
KW - ARIMA
KW - ARIMAX
KW - ERNN
KW - FFNN
KW - Forecasting
KW - Google trends
U2 - 10.1007/978-981-15-0399-3_22
DO - 10.1007/978-981-15-0399-3_22
M3 - Conference contribution/Paper
SN - 9789811503986
T3 - Communications in Computer and Information Science
SP - 272
EP - 286
BT - Soft Computing in Data Science
A2 - Berry, Michael W.
A2 - Yap, Bee Wah
A2 - Mohamed, Azlinah
A2 - Koppen, Mario
PB - Springer
CY - Singapore
ER -
