Analyzing Instagram Engagement to Forecast Domestic Tourist Trips in Lake Toba and North Sumatra: A Dual Approach with Conventional Statistics and Machine Learning Techniques - Erna Nurmawati; Teguh Sugiyarto; Navika Artiari; Adelina Rahmawati (Jurnal Kepariwisataan: Destinasi, Hospitalitas dan Perjalanan, 2024)
The tourism industry is well known as one booster for economic development. The advance of the tourism industry will lead to the improvement of other economic sectors. Therefore, the Indonesian government is taking steps to ensure the development of its tourism industry by launching 10 super-priority destinations (DSP). Despite numerous efforts and interventions, evidence suggests that the demand for the tourism industry in certain DSPs remains unsatisfied. This also holds true for Lake Toba in North Sumatra. Therefore, it is important to understand how to promote the destination site effectively and increase the number of domestic visitors. This study is aimed at assessing the impact of digital marketing through Instagram to determine the number of domestic tourist trips. The engagement rate (ER) on Instagram posts represents the impact of digital marketing. The result reveals that the topic 'cultural tourism and its activities that develop the economy' has the highest average ER, reaching 692.48. Further analysis reveals that the LSTM model, with independent variables TPK, GTI, and ER on the topic of 'ticket information and vacation packages', is the most effective model for predicting the number of domestic tourist trips to North Sumatra. This analysis emphasizes the crucial role of digital marketing to shape the demand for the tourism industry. The conclusion is based on the significant influence of the Google Trends Index (GTI) and ER on Instagram posts, which serve as a gauge for domestic visitor numbers. The related stakeholders must consider this aspect to sustain its business.