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      Peramalan Jumlah Wisatawan ASEAN di Indonesia Akibat cCovid-19 Menggunakan Analisis Intervensi

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      Date
      2025
      Author
      Faizah, Nabilah Putri Noor
      Budiarti, Retno
      Agustiani, Nur
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      Abstract
      Pandemi covid-19 memberikan dampak signifikan terhadap sektor pariwisata di Indonesia, khususnya terhadap jumlah kunjungan wisatawan ASEAN. Pembatasan perjalanan internasional dan kebijakan penanganan pandemi menyebabkan penurunan drastis jumlah wisatawan. Penelitian ini bertujuan meramalkan jumlah wisatawan ASEAN di Indonesia akibat covid-19 menggunakan analisis intervensi. Model yang digunakan adalah model Autoregressive Integrated Moving Average (ARIMA) dengan pendekatan intervensi untuk mengukur dampak pandemi serta memproyeksikan tren kunjungan di masa depan. Data yang digunakan merupakan data sekunder jumlah wisatawan ASEAN dari Badan Pusat Statistik (BPS) selama periode 2017-2023. Hasil penelitian menunjukkan bahwa model intervensi mampu menangkap pola perubahan jumlah wisatawan dengan akurasi yang baik, dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 8,21%. Model ini dapat menjadi acuan bagi pemerintah dan pelaku industri pariwisata dalam menyusun strategi pemulihan sektor pariwisata pasca pandemi.
       
      The covid-19 pandemic had a significant impact on Indonesia's tourism sector, particularly on the number of ASEAN tourists visiting the country. International travel restrictions and pandemic control policies led to a drastic decline in tourist arrivals. This study aims to forecast the number of ASEAN tourists in Indonesia due to covid-19 using Intervention Analysis. The method employed is the Autoregressive Integrated Moving Average (ARIMA) model with an intervention approach to measure the pandemic's impact and project future visitor trends. The data used in this study is secondary data from the Central Bureau of Statistics (BPS) on ASEAN tourist arrivals from 2017 to 2023. The results indicate that the intervention model effectively captures changes in tourist numbers with high accuracy, achieving a Mean Absolute Percentage Error (MAPE) of 8.21%. This model can serve as a reference for the government and tourism industry stakeholders in formulating post-pandemic recovery strategies for the tourism sector.
       
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      http://repository.ipb.ac.id/handle/123456789/163193
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      • UT - Actuaria [54]

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      Copyright © 2020 Library of IPB University
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      Indonesia DSpace Group 
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