Jurnal Aplikasi Sains Data (JASID) is a peer-reviewed scientific journal published by the Data Science Study Program at Universitas Pembangunan Nasional "Veteran" East Java (UPN "Veteran" Jatim). Serving as a dedicated platform, JASID facilitates the dissemination of knowledge and practical experiences among researchers, practitioners, and academics in the field of data science applications. The journal covers a broad spectrum of topics within data science, including but not limited to machine learning, data mining, data analysis, data visualization, and natural language processing. It also emphasizes real-world applications of data science across diverse sectors such as business, finance, healthcare, and education. Through a rigorous peer review process, JASID upholds high standards of quality and originality in its published works. The journal aims to be a valuable resource for data science professionals and enthusiasts in Indonesia, fostering interdisciplinary collaboration and enhancing public understanding of the transformative potential of data science applications. Jurnal Aplikasi Sains Data (JASID) is a peer-reviewed scientific journal dedicated to advancing knowledge and innovation in the diverse field of data science applications. The journal welcomes original research articles, comprehensive reviews, and practical case studies that contribute to the understanding and implementation of data science across various domains. JASID’s scope encompasses, but is not limited to, the following areas: Machine Learning Data Mining Data Analysis Data Visualization Natural Language Processing Cloud Computing Big Data Internet of Things (IoT) Artificial Intelligence (AI) Robotics Ethical Considerations in Data Science Application of Data Science in sectors such as Business, Finance, Healthcare, Education, and Government Objectives JASID strives to: Foster and disseminate cutting-edge research and development in data science applications, both within Indonesia and globally. Serve as a reputable platform for researchers, practitioners, and academics to exchange knowledge, experiences, and innovative ideas in data science. Promote interdisciplinary collaboration among academia, industry, and government institutions to accelerate the advancement and practical adoption of data science. Raise awareness of the transformative potential and societal benefits of data science applications.