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PEMBUATAN PETA JALUR WISATA RELIGI PETILASAN SYEKH JUMADIL KUBRO DI DESA WISATA TURGO–MERAPI Sugiarto, Eko; Hananto, Kombang Haryadi; Ramadhani, Satria; Fratama, Fhikri; Maharani, Aisyah; Sari , Francisca Vidia Kumala; Pelle, Evangelin Estevania
Warta Pariwisata Vol 23 No 2 (2025):
Publisher : Pusat Perencanaan dan Pengembangan Kepariwisataan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/wpar.2025.23.2.02

Abstract

Desa Wisata Turgo–Merapi memiliki potensi wisata religi dan aktivitas tracking. Petilasan Syekh Jumadil Kubro adalah daya tarik utama wisata religi di desa wisata yang terletak di lereng sisi selatan Gunung Merapi ini. Namun, ketiadaan informasi jalur tracking dan daya tarik di sepanjang rute menuju petilasan ini menjadi kendala dalam pengembangan pariwisata sehingga pembuatan peta tracking menjadi kebutuhan penting. Kajian ini bertujuan menyusun peta tracking yang memuat titik-titik daya tarik wisata sepanjang jalur menuju petilasan Syekh Jumadil Kubro. Metode yang digunakan adalah observasi. Luaran berupa peta tracking yang mencakup lokasi daya tarik yang ada di jalur tersebut. masyarakat. Dengan pendekatan yang terintegrasi, workshop, dan dukungan infrastruktur, Desa Wisata Ciherang memiliki potensi besar untuk berkembang menjadi desa wisata mandiri yang berdaya saing.
Comparison of Clustering Algorithms for Analyzing the Impact of Conflict on Poverty and Inflation Ramadan, M Raykah Alam; Wiransyah, Dhio Pratama; Ramadhani, Satria; Simangunsong, Rayya Ramadhan; Tania, Ken Dhita; Meiriza, Alsella; Rifai, Ahmad
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.9512

Abstract

Armed conflict can have significant impacts on the social and economic conditions of a region, particularly on poverty levels and inflation. This study aims to analyze the impact of conflict on key economic indicators using a Knowledge Management System (KMS) approach and to compare the performance of clustering algorithms in identifying underlying data patterns. The research applies clustering analysis by comparing K-Means, DBSCAN, and Hierarchical Clustering algorithms to group data based on similarities in economic characteristics. The dataset used in this study consists of several indicators, including poverty levels before and during conflict, extreme poverty rates, inflation rates, GDP changes, and currency devaluation. Data preprocessing techniques such as normalization are applied to ensure comparability among variables. The evaluation of clustering performance is conducted using Silhouette Score and Davies–Bouldin Index to determine the most effective algorithm. The results show that clustering methods are able to identify distinct grouping patterns of regions based on the level of conflict impact on economic conditions. Among the evaluated algorithms, DBSCAN demonstrates superior performance in handling complex and uneven data distributions. The analysis also indicates a consistent tendency for poverty and inflation to increase during periods of conflict, highlighting the economic vulnerability of affected regions. Furthermore, the integration of clustering results into a Knowledge Management System enables the transformation of analytical outputs into structured knowledge that can support data-driven decision making. These findings are expected to contribute to the development of more effective economic policies and analytical frameworks in conflict-affected areas.