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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang
Fachrian Bimantoro Putra
Statistics Study Program, Department of Mathematics, Faculty of Mathematics and Natural Sciences, Mulawarman University, Samarinda, Indonesia
Decision Sciences, Operations Research & Management

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FOURIER SERIES APPLICATION FOR MODELING “CHOCOLATE” KEYWORD SEARCH TRENDS IN GOOGLE TRENDS DATA Andrea Tri Rian Dani; Fachrian Bimantoro Putra; Muhammad Aldani Zen; Vita Ratnasari; Qonita Qurrota A'yun
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 11, No 1 (2023): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.11.1.2023.1-9

Abstract

In some cases of regression modeling, it is very common to find a repeating pattern. To model this, of course, the approach used must be in accordance with the characteristics of the data. The Fourier series is one of the proposed approaches, because it has advantages in modeling relationship patterns that tend to repeat, such as cosine sine waves. The Fourier series is a subset of nonparametric regression, which has good flexibility in modeling. In this study, the Fourier series approach was applied to model search trend data for the keyword "Chocolate" sourced from Google Trends. Generalized Cross-Validation (GCV) is used as model evaluation criteria. Based on the results of the analysis, the best Fourier series nonparametric regression model is obtained with the number of oscillations of five, which is indicated by the minimum GCV value.
Co-Authors Andrea Tri Rian Dani Muhammad Aldani Zen Qonita Qurrota A'yun Vita Ratnasari