Abstract

<pre>Glagah Beach is one of the tourist destinations in Kulon Progo Regency, Yogyakarta which is the most visited by tourists. Glagah Beach visitors data show that in the month of Eid Al-Fitr there was a significant increase. This shows that there is an effect of the calendar variation of Eid al-Fitr. Therefore, it is needed a method that can be used to analyze time series data which contains effects of calendar variations, that is ARIMAX method. The aim of this study are to find the best ARIMAX model and to predict the number of visitors to Glagah Beach in the future. The result shows that the best ARIMAX model was ARIMAX([24],0,0). Forecasting from January to September 2016 are 37211, 21306, 26247, 24148, 28402, 29309, 81724, 26029, and 23688 visitors.</pre><br /> Keywords: Glagah Beach; variation of calendar; Eid al-Fitr; ARIMAX.

Highlights

  • the most visited by tourists

  • that there is an effect of the calendar variation of Eid al-Fitr

  • The result shows that the best ARIMAX model was ARIMAX(,0,0

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Summary

Variabel Dummy

Regresi linear mempunyai bentuk umum yang sama dengan regresi dalam konteks runtun waktu. Sedangkan menurut Suhartono et al [8] model regresi variabel dummy untuk efek liburan dapat ditulis yt = γ0 + γ1V1,t + γ2V2,t + ⋯ + γlVl,t + wt dengan yt adalah nilai pengamatan ke-t, γl adalah parameter variabel dummy dengan efek liburan, Vl,t adalah variabel dummy dengan efek liburan, dan wt adalah eror ke-t. Variabel exogenous yang digunakan dapat berupa variabel dummy untuk efek variasi kalender dan tren deterministik. 5. Uji Signifikasi Parameter Model ARIMAX yang baik residunya harus memenuhi asumsi white noise dan berdistribusi normal. 7. Metode Penelitian Metode yang digunakan dalam penelitian ini adalah studi kasus menggunakan data bulanan banyaknya pengunjung Pantai Glagah, Kulon Progo, Yogyakarta dari tahun 2009 sampai tahun 2015 yang diperoleh dari buku Statistik Kepariwisataan Yogyakarta. B. Melakukan regresi time series untuk menghilangkan efek tren, variasi kalender, dan efek musiman dengan variabel dummy.

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