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All Journal International Journal of Artificial Intelligence Research Journal of Research in Social Science and Humanities
Kindiasari, Aktansi
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Fashion as an Expression of Cultural Identity in the Digital Age Wardaya, Awwali Ibnu; Bestari, Afif Ghurub; Sulistiyanto, Sulistiyanto; Kindiasari, Aktansi
Journal of Research in Social Science and Humanities Vol 4, No 1 (2024)
Publisher : Utan Kayu Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/jrssh.v4i1.118

Abstract

Fashion has long been a powerful medium for expressing cultural identity, reflecting various communities' values, traditions, and social dynamics. This expression has evolved dramatically in the digital age, shaped by the pervasive influence of technology and social media. This study explores how fashion serves as a conduit for cultural identity in the contemporary digital landscape. It examines the interplay between traditional fashion practices and modern digital platforms. It highlights how individuals and communities use fashion to navigate and assert their cultural identities in an increasingly globalised world. The research investigates the role of digital platforms, such as Instagram, TikTok, and fashion blogs, in disseminating and transforming cultural fashion trends. These platforms provide a space for cultural exchange and the democratisation of fashion, allowing underrepresented voices to showcase their heritage and creativity. Additionally, the study delves into the impact of virtual fashion shows, digital influencers, and online retail on cultural identity expression. It considers how these elements contribute to preserving and evolving traditional fashion practices. Furthermore, the research addresses the complexities of cultural appropriation in the digital age, where fashion trends can be rapidly adopted and commercialised, often detached from their cultural significance. By analysing case studies and engaging with fashion designers, influencers, and consumers, the study offers insights into the ethical considerations and responsibilities involved in cultural fashion representation. The findings suggest that while digital platforms can facilitate celebrating and sharing cultural identities, they pose challenges related to authenticity, appropriation, and commercialisation. This duality underscores the need for a nuanced understanding of fashion as a cultural expression in the digital era. The study concludes with recommendations for fostering a more inclusive and respectful digital fashion ecosystem that honours and preserves cultural identities while embracing innovation and diversity. Through this exploration, the research aims to contribute to the broader discourse on cultural identity, fashion, and digital media, offering valuable perspectives for academics, industry professionals, and cultural advocates.
Development of Human Resource Management Information System to Improve Employee Performance Efficiency and Effectiveness Oktaviannur, Moh.; Kindiasari, Aktansi
International Journal of Artificial Intelligence Research Vol 8, No 1.1 (2024)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v8i1.1.1198

Abstract

The development of a Human Resource Management Information System (HRMIS) aims to enhance the efficiency and effectiveness of employee performance. This study focuses on designing and implementing an integrated HRMIS that automates various HR functions such as recruitment, attendance tracking, performance evaluation, and employee development. By leveraging advanced information technologies, the HRMIS provides real-time data and analytics, facilitating informed decision-making and strategic planning for HR managers. The system's user-friendly interface ensures ease of use and accessibility, promoting higher adoption rates among employees and management. Empirical data collected from case studies and surveys conducted within organizations demonstrate significant improvements in operational efficiency, reduced administrative burden, and enhanced employee satisfaction and productivity. The findings suggest that a well-implemented HRMIS can be a critical tool in optimizing human resource processes, aligning HR strategies with organizational goals, and ultimately driving overall business performance. Future research should explore the integration of emerging technologies such as artificial intelligence and machine learning to further enhance the capabilities of HRMIS.
Application of Computer Vision and Pattern Recognition in Automated Quality Inspection of Industrial Products Nurdiyanto, Heri; Kindiasari, Aktansi; Sulistiyanto, Sulistiyanto
International Journal of Artificial Intelligence Research Vol 9, No 2 (2025): December
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i2.1507

Abstract

Quality inspection is a critical process in industrial production to ensure that products meet predefined standards and specifications. Traditionally, quality inspection has relied heavily on manual visual checks, which are time-consuming, subjective, and prone to human error. This study explores the application of computer vision and pattern recognition techniques to develop an automated quality inspection system for industrial products. The proposed system employs high-resolution cameras and image processing algorithms to capture and analyze visual features of products in real-time on the production line. Key techniques utilized include feature extraction, edge detection, and texture analysis to identify defects such as scratches, dents, and dimensional inaccuracies. Pattern recognition algorithms, such as support vector machines (SVM) and convolutional neural networks (CNN), are trained on large datasets of product images to classify items as acceptable or defective with high accuracy. The system was tested on a dataset collected from a manufacturing facility producing metal components. Experimental results demonstrate that the automated system achieved an inspection accuracy of 98%, significantly outperforming manual inspection methods in terms of speed and consistency. Furthermore, the integration of this system into the production line reduced inspection time by approximately 70% and minimized production downtime. This research highlights the potential of intelligent informatics, particularly computer vision and pattern recognition, in enhancing the efficiency, reliability, and scalability of industrial quality control processes. The findings suggest that such automated systems can contribute significantly to the advancement of Industry 4.0 by enabling smart manufacturing practices and reducing dependence on manual labor. Future work will focus on extending the system to handle more complex products and dynamic production environments
Co-Authors Bestari, Afif Ghurub Moh. Oktaviannur, Moh. Nurdiyanto, Heri Sulistiyanto Sulistiyanto, Sulistiyanto Wardaya, Awwali Ibnu