Studi literatur tentang pemanfaatan prophet dalam klasifikasi data time series
Keywords:
klasifikasi, deret waktu, facebook prophet, tinjauan pustakaAbstract
Abstrak
Data deret waktu digunakan secara luas di berbagai industri. Namun, proses klasifikasi ini sering kali terhambat oleh tren, musiman, dan fluktuasi kompleks yang ada dalam data. Facebook Prophet adalah salah satu model peramalan deret waktu yang efektif untuk menangkap pola tren dan musiman. Akan tetapi, model ini tidak dirancang sebagai algoritma klasifikasi. Penelitian ini bertujuan untuk mengkaji secara kritis bagaimana Prophet dimanfaatkan untuk mendukung kegiatan klasifikasi terkait data deret waktu melalui studi tinjauan literatur. Metode yang diterapkan adalah tinjauan literatur terhadap 30 artikel ilmiah terbitan dari berbagai bidang aplikasi yang bekerja dalam periode 2020–2025. Temuan studi menunjukkan bahwa Prophet terutama digunakan pada tahap awal peramalan untuk menangkap pola tren dan musiman. Model ini menghasilkan residu yang kemudian diolah dengan berbagai metode seperti ambang batas, berbasis aturan, atau pemodelan ensemble, dikombinasikan dengan metode seperti Decision Tree (DT); serta metode deep learning seperti LSTM dan algoritma peningkatan gradien seperti LightGBM, bersama dengan pendekatan hibrida. Teknik-teknik tersebut berhasil meningkatkan kinerja klasifikasi data terutama ketika bekerja dengan pola yang sangat periodik. Namun, semua ini datang dengan biaya kompleksitas dan komputasi yang lebih tinggi. Penelitian ini menyimpulkan bahwa Prophet memainkan peran penting dalam klasifikasi data, meskipun metode lanjutan deret waktu perlu diadopsi sesuai dengan karakteristik data dan tujuan analisis.
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References
Daftar Pustaka
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