Implementasi Algoritma K-Means Untuk Pengelompokkan Destinasi Wisata Kabupaten Tegal

Yuni, Novita Br. Sihaloho (2023) Implementasi Algoritma K-Means Untuk Pengelompokkan Destinasi Wisata Kabupaten Tegal. Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

Tourism is an important sector that contributes to increasing national income, providing employment, and contributing to foreign exchange. With the development of tourism in each region, the local government can take advantage of this opportunity to maximize the potential of natural resources. Tegal Regency is one of the regencies in Central Java. Tegal Regency has many water tourism destinations such as Guci Hot Springs, Taman Rakyat Slawi, Semedo Museum, and many others. Disporapar of Tegal Regency has difficulty in grouping tourist destinations because currently there is no technique used in grouping. The purpose of this research is to provide a solution to the Tegal Regency Youth, Sports, Culture and Tourism Office regarding the grouping of tourist destinations in the region. The method used in this study to classify tourist destinations is the K-Means Clustering Algorithm. Aims to group similar objects or products into different groups. K-Means Clustering is a technique used in data mining. Data mining is one of computer science that is used to retrieve certain information obtained from very large databases. The results obtained were 16 destinations classified as quite popular (C0), 37 destinations classified as less popular (C1), and 2 destinations classified as popular (C2) based on the attributes of entrance ticket prices, number of visits and amount of infrastructure. The benefits of grouping tourist destinations as a consideration for the local government in developing and evaluating the development of tourist destinations in Tegal Regency. Keywords: Tourism, Data Mining, K-Means Clustering

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