Prediksi Turis Mancanegara ke Indonesia Menggunakan Metode EDA Time Series dan LSTM

Westlie Wiratama(1*), Lutfi Aulia Alifah(2), Alta Gurusinga(3), Evta Indra(4),

(1) Universitas Prima Indonesia, Indonesia
(2) Universitas Prima Indonesia, Indonesia
(3) Universitas Prima Indonesia, Indonesia
(4) Universitas Prima Indonesia, Indonesia
(*) Corresponding Author

Abstract


Indonesia experienced a decline in the number of tourists, with a 74.9 percent decrease in tourist arrivals in 2020 compared to 2019, which had a significant impact on the country's economy. However, in 2022, as Indonesia and the world were moving towards a normalization phase, the country began to see an increase in tourist visits. The exact number of tourists cannot be determined, but it is crucial to predict and forecast the future patterns of tourist arrivals so that the government and travel agencies can make informed decisions regarding policy changes. Therefore, the research problem in this study is how to apply the Exploratory Data Analyst (EDA) method and Long Short Term Memory (LSTM) to explore and predict the patterns of tourist arrivals in the future, providing guidance for determining appropriate policies. Based on the EDA results, the majority of tourist visits come from the Asian continent, with Malaysia contributing the highest number of tourists, followed by China and Timor-Leste. On the other hand, the LSTM method predicts that the highest number of tourist arrivals will occur in August 2024, with 580,000 visitors from the Asian continent, and in May 2025, with 580,000 visitors from ASEAN countries. The Mean Absolute Percentage Error (MAPE) for the LSTM method is 13.84 for the Asian continent and 15.96 for ASEAN countries.

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DOI: http://dx.doi.org/10.30645/jurasik.v8i2.637

DOI (PDF): http://dx.doi.org/10.30645/jurasik.v8i2.637.g610

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