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All Journal Regula Fidei : Jurnal Pendidikan Agama Kristen DoubleClick : Journal of Computer and Information Technology Journal of Intelligent Decision Support System (IDSS) Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat International Journal of Computer and Information System (IJCIS) Unram Journal of Community Service (UJCS) Transformasi Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Pengabdian Pancasila (JPP) Jurnal Masyarakat Mengabdi Nusantara Electronic Journal of Education, Social Economics and Technology Jurnal Pengabdian Masyarakat Bangsa Jurnal Kabar Masyarakat Green Engineering: Journal of Engineering and Applied Science Jurnal Teknik Informatika dan Teknologi Informasi
Kanafi Kanafi
STMIK Bina Patria
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Optimization of Clustering Model for Mapping Tourism Potential in Magelang Regency Using K-Means Clustering Algorithm Kanafi Kanafi; Fatkhurrochman Fatkhurrochman
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1011

Abstract

Magelang Regency has various tourist destinations with highly diverse potentials, including nature, history, culture, and religious tourism. However, the management of these tourism potentials still faces serious challenges, particularly in terms of mapping, which has not been well-structured. The numerous different tourist spots with various regional potentials have led to local and international tourists experiencing difficulties in selecting promising destinations. The role of mapping for clustering tourism potentials has become a primary need to accelerate economic growth in Indonesia. If clustering is conducted conventionally, without being based on in-depth data analysis, it can risk producing policies that are not well-targeted. The objective of this study is to map the tourism potentials in Magelang Regency using the optimization of the K-Means Clustering method. This clustering is based on variables: attractiveness, accessibility, facilities, number of visitors, ticket prices, security, and rating values. The research methods include literature review, data collection, data pre-processing, K-Means algorithm implementation and optimization, model evaluation and validation, system visualization development, testing, reporting, and publication. The final result of this study is the clustering of tourism potentials into three 7 clusters, the Silhouette Coefficient test yielded a score of 0.504.
Co-Authors achiriyana, ita Cisilia Sundari Dwi Astuti Dwi ASTUTI Emha Taufiq Luthfi Farida, Maraiati Fatimah Nur Arifah Fatkhurrochman Fatkhurrochman Fatkhurrochman Fatkhurrochman Fatkhurrochman, Fatkhurrochman handayani, riska dwi Kapti Kapti Karindra Triwulandari Kusrini Kusrini Mira Fitriana Muhammad Abdul Muin Muhammad Lutfi Mahasinul Akhlak Muhammad Riza Eko S Pujiono, Andrias Riska Dwi Handayani Rony Syaifullah, Rony Sugeng Wahyudiono Sukris Sutiyatno Tri Yusnanto Vinindina Meita Widyasri Yeza Febriani Yulmiawati, Yulmiawati Yusuf Wahyu Setiya Putra