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All Journal Bulletin of Computer Science Research AT-TAKLIM: Jurnal Pendidikan Multidisiplin
Beki Subaeki
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Computer Science & IT Other

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PENGUKURAN KESIAPAN IMPLEMENTASI TEKNOLOGI HYPER-CONVERGED INFRASTRUCTURE DI RUMAH SAKIT BANDUNG RAYA BERDASARKAN MODEL TRI 2.0 DAN TAM Tauchida Winanda Fadjar Setiawan; Khaerul Manaf; Beki Subaeki; Raden Muhammad Adrian Septiandry; Yanyan Gunawan
AT-TAKLIM: Jurnal Pendidikan Multidisiplin Vol. 2 No. 8 (2025): At-Taklim: Jurnal Pendidikan Multidisiplin (Edisi Agustus)
Publisher : PT. Hasba Edukasi Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71282/at-taklim.v2i8.888

Abstract

Efficient information technology management has become a primary necessity for hospitals. One emerging solution is Hyper-Converged Infrastructure (HCI), which integrates computing, storage, and networking into a single platform. This study aims to assess the readiness of hospitals in the Bandung Raya region to adopt HCI, using the Technology Readiness Index (TRI) 2.0 and the Technology Acceptance Model (TAM) as the analytical framework. TRI 2.0 encompasses four psychological dimensions: optimism, innovativeness, discomfort, and insecurity. TAM is employed to evaluate perceived ease of use and perceived usefulness of the technology. The research method is quantitative, utilizing a questionnaire survey distributed to IT personnel and hospital management. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that optimism and innovativeness positively influence technology perception, while discomfort and insecurity act as psychological barriers. Positive perceptions of ease of use and usefulness further enhance readiness for HCI implementation.
Implementasi Algoritma K-Means Clustering untuk Identifikasi Lokasi Strategis Coffee Shop Rohman, Lahuri Gofarana; Cecep Nurul Alam; Beki Subaeki
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.600

Abstract

The rapid growth of coffee shops in Bandung City has led to increasingly fierce competition among business owners, particularly in choosing strategic locations. Inappropriate location selection can negatively impact customer attraction and business sustainability. This study aims to identify strategic areas for coffee shop development in Bandung City using the spatial-based K-Means Clustering algorithm. The data used consists of active food establishment locations obtained from the Open Data Kota Bandung portal, which includes latitude and longitude information. The K-Means algorithm with K-Means++ initialization was used to group the restaurant locations into three clusters based on geographical proximity. The clustering process was carried out in two iterations, beginning with the initial centroid determination, distance calculation using the Euclidean formula, and centroid updates until convergence. Final results show that the areas of Jl. Aceh Cluster 0 at coordinates (-6.911431, 107.622713), Jl. Setiabudi Cluster 1 at coordinates (-6.879891, 107.600774), and Jl. Kebon Jati Cluster 2 at coordinates (-6.917228, 107.598990) have different strategic potentials suited to specific coffee shop concepts. Evaluation was conducted through spatial distribution visualization, minimum distance analysis, and cluster stability. This study confirms that the K-Means method is effective in supporting spatial-based decision-making for business development.
Co-Authors Cecep Nurul Alam Khaerul Manaf Raden Muhammad Adrian Septiandry Rohman, Lahuri Gofarana Tauchida Winanda Fadjar Setiawan Yanyan Gunawan