About the Journal
Data Science Insights, with ISSN 3031-1268 (Online) published by PT Visi Media Ntework is a journal that publishes Focus & Scope research articles, which include
Data Science and Machine Learning; Data Science and AI; Blockchain and Advance Data Science; Cloud computing and Big Data; Business Intelligence and Big Data; Statistical Foundation for Data Science; Probability and Statistics for Data Science; Statistical Inference via Data Science; Big Data and Business Analytics; Statistical Thinking in Business; Data Driven Statistical Methods; Statistical Methods for Spatial Data Analytics; Statistical Techniques for Data Analysis; Data Science in Communication; Information and Communication Technology; Graph Data Management for Social Network Applications; Metadata for Information Management; Information/Data: Organization and Access; Information Science and Electronic Engineering; Big Data and Social Science; Data Communication and Computer Network; ICT & Data Analytics.
The aim of Data Science Insights is to provide a platform for researchers, academicians, professionals, and practitioners to share and disseminate innovative ideas, empirical findings, and theoretical advances in the field of data science and its multidisciplinary applications. The journal seeks to promote the integration of data science methodologies with artificial intelligence, big data analytics, business intelligence, and information technology to address contemporary challenges and support decision-making processes across various sectors.
Through rigorous peer review and publication, Data Science Insights aims to enhance the understanding and development of data-driven solutions, encourage collaboration between academia and industry, and contribute to the advancement of science, technology, and society.
This journal is published by the PT Visi Media Network, which is published twice a year.
Data Science Insights © 2023 by PT Visi Media Network is licensed under CC BY-SA 4.0
Current Issue
Articles
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Digital Data Collection among Low ICT-Literate Rural Communities: A Case Study using Google Forms via Smartphones
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Abstract Views : 183  
PDF Downloads : 76
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Assessing the Efficiency and Accuracy of K-Means Clustering Compared to Other Clustering Techniques
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Abstract Views : 168  
PDF Downloads : 82
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Predicting Student Performance using Linear Regression
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Abstract Views : 128  
PDF Downloads : 57
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Comprehensive Approach to Weather Prediction with the Random Forest Algorithm
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Abstract Views : 121  
PDF Downloads : 58
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Cluster Analysis of Superstore Data using K-Means and K-Medoids for Product Delivery Insights
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Abstract Views : 123  
PDF Downloads : 50
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Comparative Analysis of Data Visualization Techniques for Rainfall Data
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Abstract Views : 134  
PDF Downloads : 48
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