PREDIKSI POTENSI WISATA MENGGUNAKAN ALGORITMA RANDOM FOREST DI KABUPATEN GAYO LUES: TOURISM POTENTIAL PREDICTION USING RANDOM FOREST ALGORITHM IN GAYO LUES DISTRICT - Mhd Sultan; Eva Darnila; Yesy Afrillia (Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, 2025)
Gayo Lues Regency is one of the regions in Aceh Province that possesses natural and cultural wealth with the potential to be developed as a leading tourist destination. However, the tourism potential in this region has not been fully mapped and optimally utilized due to the lack of data-based information and appropriate management strategies. This study aims to address these challenges by applying a quantitative approach using the Random Forest method to analyze and predict tourism potential. The research involved data from 30 tourist destinations, divided into 80% training data and 20% test data. The research stages consisted of data collection, preprocessing, model training, and model evaluation. The results indicate that the Random Forest method demonstrated good performance in predicting tourism potential, with the most influential variables being the number of visitors (59.79%), rating (13.40%), distance to the city (9.28%), and road access (5.15%). The classification results show that 14 tourist attractions (46.67%) are in the Medium category, which indicates good potential but still requires improvements in facilities, access, and promotion. Furthermore, 9 attractions (30%) fall into the High category and are ready to be developed as leading destinations, while 7 attractions (23.33%) are categorized as Low and need further evaluation regarding their feasibility and development strategies.