PENERAPAN ALGORITMA XGBOOST DALAM PENENTUAN POTENSI SEKTOR WISATA LOKAL DI LOMBOK TIMUR

Wenti Ayu Wahyuni; Muh. Nasirudin Karim; Zumratul Muahidin

Authors

Wenti Ayu Wahyuni Universitas Teknologi Mataram
Muh. Nasirudin Karim Universitas Teknologi Mataram, Mataram, Indonesia
Zumratul Muahidin Universitas Teknologi Mataram, Mataram, Indonesia

Keywords:

XGBoost, tourism potential, classification, machine learning, East Lombok

Abstract

East Lombok holds significant tourism potential, yet its development faces challenges due to the lack of data-driven spatial analysis. This study applies the XGBoost algorithm to predict and classify tourism potential based on features such as visitor numbers, facilities, accessibility, digital exposure, and sociocultural indicators. The results show that XGBoost achieves a classification accuracy of 92%, with review ratings and digital activity being the most influential factors. Spatial visualization of the prediction highlights regions with high, medium, and low potential. This approach offers a data-driven tool to support more targeted and effective tourism development strategies.

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