Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Future Academia The ...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
addClaim

Peramalan Kedatangan Wisatawan Macanegara ke Provinsi Bali ‎Menggunakan Metode Singular Spectrum Analysis (SSA)‎

Authors: Sri Yuliana; Raihanah Rafidah; Gumgum Darmawan;

Peramalan Kedatangan Wisatawan Macanegara ke Provinsi Bali ‎Menggunakan Metode Singular Spectrum Analysis (SSA)‎

Abstract

Pariwisata Bali adalah sektor strategis dalam berperan penting terhadap perekonomian nasional, ‎khususnya sebagai penyumbang utama devisa negara dan lapangan kerja. Fluktuasi jumlah ‎wisatawan mancanegara sangat dipengaruhi oleh faktor musiman, dinamika ekonomi global, ‎perubahan tren pariwisata internasional, serta guncangan eksternal seperti krisis ekonomi dan ‎pandemi. Oleh karena itu, analisis peramalan wisatawan menjadi penting untuk memahami pola ‎kunjungan dan mendukung perencanaan kebijakan pariwisata yang adaptif dan berkelanjutan. Tujuan dari penelitian ini adalah melakukan peramalan terhadap jumlah wisatawan ke Bali dengan menggunakan pendekatan Singular Spectrum Analysis (SSA). Data bulanan kedatangan wisatawan (2009–2025) dianalisis dengan ‎SSA. Evaluasi akurasi dilakukan menggunakan MAPE. Model peramalan jumlah wisatawan ‎mancanegara di Provinsi Bali menghasilkan nilai MAPE sebesar 7,23%, yang termasuk kategori ‎sangat baik menurut Lewis (1982). Model berhasil menangkap pola tren utama dan fluktuasi ‎jumlah wisatawan dengan baik, dengan tingkat kesesuaian tinggi antara data aktual dan hasil ‎prediksi.‎

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid