Saputra, Faizal Dwi and , Azizah Fatmawati, M.Cs., S.T. (2026) Clustering Destinasi Wisata Berdasarkan Popularitas Dan Harga Tiket Menggunakan Metode K-Means. Skripsi thesis, Universitas Muhammadiyah Surakarta.
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Abstract
Yogyakarta is a city with diverse tourist attractions, making it a favorite destination. With the advancement of digital technology, it’s increasingly easy to find information about various tourist attractions online. A common problem is confusion when choosing a destination due to the sheer number of options. This study aims to help categorize tourist destinations in Yogyakarta, making it easier for tourists to choose the right destination. To address this, a more sophisticated analytical technique, such as cluster analysis, is required. This study applies the K-Means clustering method. The analysis process utilizes datasets from Kaggle. The expected outcome of this study is the formation of tourist destination clusters based on specific characteristics, resulting in more structured recommendations and assisting tourists in making effective decisions. The analysis revealed three clusters: C0: paid tourism with high popularity of 188 destinations, C1: paid tourism with low popularity of 131 tourist destinations, and C2: free tourism with medium popularity of 131 tourist destinations. These clustering results provide structured destination recommendations and help travelers choose destinations based on their preferences.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Clustering, data mining, k-means, tourist destinations |
| Subjects: | T Technology > Information Technology > Software. Aplication > Data Manajemen T Technology > Information Technology T Technology > Information Technology > Software. Aplication T Technology > Information Technology > Software. Aplication > Software Engineering |
| Divisions: | Fakultas Komunikasi dan Informatika > S1 Teknik Informatika |
| Depositing User: | FAIZAL DWI SAPUTRA |
| Date Deposited: | 07 Aug 2026 02:56 |
| Last Modified: | 07 Aug 2026 02:56 |
| URI: | http://eprints.ums.ac.id/id/eprint/146796 |
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