Laurencia, Vienesca (2019) Peramalan Minat Kosmetik Herbal K-Beauty Brands Di Indonesia Berdasarkan Data Google Trends Dengan Metode ARIMAX Dan Elman RNN. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Salah satu tren makeup yang berkembang pesat di dunia adalah kosmetik herbal Korean Makeup atau yang lebih dikenal dengan istilah k-beauty yang penyebarannya dibawa oleh aktor dan aktris Korean Pop atau Korean Drama. Peminatan k-beauty melalui online dapat dideteksi dengan frekuensi pencarian kata kunci terkait k-beauty yang diakses oleh pengguna internet di Indonesia yang dapat diidentifikasi melalui google trends. Penelitian ini bertujuan untuk melakukan peramalan minat lima produk k-beauty dengan menggunakan metode peramalan statistik, ARIMAX, FFNN dan Elman RNN. Lima produk k-beauty yang digunakan adalah Laneige, Etude House, Nature Republic, Tony Moly dan Innisfree berdasarkan pencarian data google trends periode September 2012 hingga September 2018 yang memiliki pola data linier dimana terjadi intervensi pada pencarian Nature Republic. Penelitian ini menunjukkan bahwa metode terbaik untuk peramalan hasil pencarian produk Etude House dan Tony Moly adalah Exponential Smoothing, kemudian metode terbaik untuk pencarian produk Laneige, Nature Republic, dan Innisfree secara berturut-turut adalah ARIMAX, FFNN dan Elman RNN. Penelitian ini menunjukkan bahwa bahwa model yang lebih rumit tidak selalu mengahasilkan peramalan yang lebih baik dibandingkan model sederhana.
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One of the fastest growing makeup trends in the world is Herbal Korean Makeup, well known as k-beauty, which is carried out by Korean Pop or Korean Drama actors and actresses. The interest of k-beauty through online can be detected by the frequency of a keyword related to k-beauty accessed by internet users in Indonesia that can be identified through google trends. The objective of this study is to forecast the interest of five k-beauty products using statistical forecasting methods, ARIMAX, FFNN and Elman RNN. The five k-beauty products used are Laneige, Etude House, Nature Republic, Tony Moly and Innisfree based on google trends data search for the period September 2012 to September 2018 which have a liniear pattern and intervention effect in Nature Republic. This research shows that Exponential Smoothing is the best method to predict Etude House and Tony Moly products. For Laneige, Nature Republic, and Innisfree products, the best method are ARIMAX, FFNN, and Elman RNN respectively. This research shows that complex models do not always give a better result than the simple one.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 519.53 Lau p-1 2019 |
| Uncontrolled Keywords: | ARIMAX, FFNN, Elman RNN, k-beauty, google trends, kosmetik herbal |
| Subjects: | H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA280 Box-Jenkins forecasting |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Laurencia Vienesca |
| Date Deposited: | 24 Nov 2021 04:11 |
| Last Modified: | 24 Nov 2021 04:11 |
| URI: | http://repository.its.ac.id/id/eprint/61600 |
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