PENERAPAN METODE K-MEANS UNTUK PENGELOMPOKAN DATA KUNJUNGAN WISATA PADA DINAS KEBUDAYAAN DAN PARIWISATA PROVINSI JAMBI Tourism, K-Means, clustering, Python, Orange.

Abstract

Tourism is a vital economic sector in Indonesia, including in Jambi City, which contributes significantly to regional income and increasing employment. However, the management of tourist visit data at the Jambi Provincial Culture and Tourism Office is still done manually, making it difficult to obtain accurate information on tourist trends and their preferences. These constraints include the limitations of modern information technology and the lack of application of data analysis methods such as clustering, which hinders the effectiveness of strategic decision making. This study proposes the application of the K-Means clustering method to group tourist visit data based on characteristics such as tourist origin, purpose of visit, and type of destination. The Orange data analysis tool is used to accelerate the analysis and visualization process, resulting in in-depth and strategic insights. With the integration of Orange and Python, data analysis can be more flexible and tailored to needs. This approach is expected to improve the management of tourist visit data, help identify tourist patterns, and support more effective tourism development in Jambi Province.