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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi
Rizki Hesananda
Universitas Siber Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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THE ROLE OF INFORMATION SYSTEMS IN ADVANCING SMART VILLAGES: A RURAL TOURISM CASE STUDY Agus Trihandoyo; Rizki Hesananda; Kushandajani Kushandajani; Firman Muhksin
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 2 (2024): JITK Issue February 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i2.5044

Abstract

Recent studies highlight the need for a deeper understanding of the ways in which information systems, local government policy and community involvement affect the development of rural tourism. By using Structural Equation Modelling and Partial Least Squares (SEM-PLS), the current study aims to analyze the role of information systems, local government policy and local community engagement in rural tourism development. Using data from 69 participants in Watesjaya village, Bogor regency, the study analyzes multiple relationships among latent constructs. The data, encompassing variables such as system quality, information quality, local government policy, local community engagement, destination branding, and rural tourism development, undergoes meticulous reliability and validity assessments. Results from the SEM-PLS analysis unveil significant relationships and insights. Local community engagement emerges as a pivotal factor, positively influencing tourist satisfaction (0.499) and moderately affecting destination branding (0.239). However, local government policy exhibits a less pronounced positive impact on tourist satisfaction (0.069847) and a notable negative influence on destination branding (-0.300460), underscoring the need for policy realignment. Information quality paradoxically influences tourist satisfaction negatively (-0.185) and destination branding (-0.158), highlighting areas for strategic improvement. Meanwhile, information system quality positively affects tourist satisfaction (0.055) and significantly contributes to rural tourism development (0.783). This study provides a better understanding of stakeholders about rural tourism development by focusing on information system quality, information quality, local government policies, and local community engagement The study indicates that information system quality and local community engagement can be valuable indicators for boosting rural tourism development and improving tourist satisfaction.
Study of Awareness Patterns of Credit Card Users towards Ads with K-Means Clustering Algorithm Rizki Hesananda; Alfi Prabowo
Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Volume 7 Number 2 (2025)
Publisher : Fakultas Teknik Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/asiimetrik.v7i2.8295

Abstract

In the era of digital transformation, credit cards have become an essential component of modern financial life, where users’ understanding of card features significantly influences their financial decisions. Despite the wide use of advertising in the financial sector, limited studies have explored how credit card users in emerging markets respond to such campaigns. Addressing this gap, this study analyzes advertisement awareness patterns among credit card users in Indonesia using the K-Means Clustering algorithm on a dataset collected from August 2023 to March 2024. The study aims to examine levels of advertisement awareness, segment users based on their responses, and assess the implications of these segments for marketing strategies. The methodology follows the Knowledge Discovery in Database (KDD) process: data selection, preprocessing, transformation, clustering with K-Means, and evaluation using the Silhouette Score. Results reveal three distinct user clusters: (1) highly aware users in large cities with high exposure; (2) moderately aware users from mid-tier cities; and (3) low-awareness users despite high exposure, often from older age groups and lower SES backgrounds. The clustering yielded Silhouette Scores above 0.60, validating segmentation quality. The novelty lies in applying machine learning to segment awareness levels using a multi-city real-world dataset. The findings offer practical value for credit card providers to enhance targeted campaigns, improve user engagement, and allocate marketing resources more effectively across demographic segments.
Co-Authors Agus Trihandoyo Alfi Prabowo Firman Muhksin Kushandajani .