Prediksi Jumlah Wisatawan Asing Masuk ke Indonesia Tahun 2026 Menggunakan Model Rantai Markov - Anggi Nur Ananda Saragih; Widi Ningsih Panggabean; Melissa Chandra; Agnes Yulia Saragih; Sudianto Manullang; Alvi Sahrin Nasution; Mizan Hasibuan (Griya Journal of Mathematics Education and Application, 2025)
Indonesia's tourism sector experienced a drastic decline due to the pandemic, with the number of foreign tourists falling by 64.64% in 2020, disrupting contributions to the country's GDP and foreign exchange. The lack of application of stochastic models to predict foreign tourist arrivals nationwide is a challenge in policy planning. This research aims to build a Markov Chain-based prediction model to estimate the number of foreign tourists in 2026, overcoming the weaknesses of conventional approaches that are deterministic. The method used is the analysis of the probability of transition between states (Increase/Decrease/Stable) based on historical data of tourist arrivals. The prediction results show that the number of foreign tourists in 2026 reached 18,202,215 people, indicating an optimistic growth trend and potential recovery of the tourism sector. The conclusion of this study confirms that the Markov Chain model is effective for macro projection of tourist fluctuations, so that it can be a reference in the preparation of adaptive and data-based tourism policies.