https://ijdasea.upnjatim.ac.id/index.php/ijdasea/issue/feed IJDASEA (International Journal of Data Science, Engineering, and Analytics) 2024-12-02T03:12:34+00:00 Dr. Eng. Ir. Dwi Arman Prasetya, ST., MT., IPU. arman.prasetya.sada@upnjatim.ac.id Open Journal Systems https://ijdasea.upnjatim.ac.id/index.php/ijdasea/article/view/23 Navigating The Duality: Privacy And Security Concerns In Knowledge Management Systems (KMS) 2024-11-19T02:28:45+00:00 Iswanda Fauzan Satibi satibi.if@upnjatim.ac.id Ragil Tri Atmi ragil.tri.atmi@fisip.unair.ac.id <p><span style="font-weight: 400;">This study delves into the intricate relationship between privacy and security within Knowledge Management Systems (KMS). It identifies and analyzes distinct employee perceptions of these intertwined issues within a company's KMS environment. By exploring these perspectives, the authors aim to dispel the confusion surrounding privacy and security in KMS settings. The research employed an explanatory sequential mixed method design.&nbsp; First, a questionnaire survey was distributed directly to KM staff across three companies. This was followed by semi-structured interviews with four KM staff members. The findings reveal a high level of employee awareness regarding the importance of KMS and, consequently, the significance of personal information privacy and security. The study further distinguishes between privacy and security concerns within KMS. Privacy concerns, differentiated across three dimensions: confidentiality, trust, and behavior, are primarily viewed from the organizational layer. Security aspects, on the other hand, are seen as aligned with the ICT layer, governed by legal frameworks and KMS architecture.</span></p> 2024-12-02T00:00:00+00:00 Copyright (c) 2024 Iswanda Fauzan Satibi, Ragil Tri Atmi https://ijdasea.upnjatim.ac.id/index.php/ijdasea/article/view/24 Wayang’s Images Recognition using Vision Transformer 2024-11-19T01:52:38+00:00 Andreas Nugroho Sihananto andreas.nugroho.jarkom@upnjatim.ac.id Muhammad Muharrom Al Haromainy muhammad.muharrom.if@upnjatim.ac.id Zaky Ahmad Fauzi 22081010282@student.upnjatim.ac.id Reno Alfa Reza 23081010091@student.upnjatim.ac.id Gredy Christian Hendrawan Putra 22081010195@student.upnjatim.ac.id Theressa Marry Christianty 23081010131@student.upnjatim.ac.id <p class="MDPI17abstract" style="margin-top: 0cm; line-height: normal;"><em><span style="font-size: 10.0pt;">Due to its complex nature and outdated perception, Wayang is a traditional Indonesian art form influenced by Hindu-Buddhism. However, it is difficult for the younger generation to recognize the various types of Wayang. In an effort to preserve Wayang culture, this study evaluates the performance of four deep learning models in recognizing types of Wayang namely, Vision Transformer (ViT), ResNet34, YOLOv5-cls, and YOLOv8-cls. These models were trained and assessed using a dataset of 232 images representing six Wayang types and using matrix such as accuracy, recall, precision, and F1 score. ViT demonstrated efficiency and adaptability despite high computational requirements, achieving the best accuracy (91.3%), showing high adaptability despite substantial computational requirements. Meanwhile, YOLOv5-cls and YOLOv8-cls offered a good balance betwwen accuracy and efficiency. This study suggest that deep learning models can play an essentialrole in Wayang by enhancing recognition accessibility, thus helping younger generations appreciate this tradisional art form.</span></em></p> 2024-12-02T00:00:00+00:00 Copyright (c) 2024 Andreas Nugroho Sihananto, Muhammad Muharrom Al Haromainy , Zaky Ahmad Fauzi, Reno Alfa Reza, Gredy Christian Hendrawan Putra; Theressa Marry Christianty