Predictive Analysis in Business Analytics: Application of Decision Tree in Business Decision Making


  • Chee Sun Lee School of Management, University Sains Malaysia Corresponding Author
  • Peck Yeng Sharon Cheang School of Management, ,11800 USM, Penang, Malaysia Corresponding Author



Business Analytics (BA), Predictive Analysis (PA), Machine Learning (ML), Decision Tree (DT)


Business Analytics was defined as one of the most important aspects of combinations of skills, technologies and practices which scrutinize a corporation’s data and performance to transpire a data driven decision making analysis for a corporation’s future direction and investment plans. In this paper, much of the focus will be given to the predictive analysis which is a branch of business analytics which scrutinize the application of input data, statistical combinations and intelligence machine learning (ML) statistics on predicting the plausibility of a particular event happening, forecast future trends or outcomes utilizing on hand data with the final objective of improving performance of the corporation. Predictive analysis has been gaining much attention in the late 20th century and it has been around for decades, but as technology advances, so does this technique and the techniques include data mining, big data analytics, and prescriptive analytics. Last but not least, the decision tree methodology (DT) which is a supervised simple classification tool for predictive analysis which be fully scrutinized below for applying predictive business analytics and DT in business applications

Author Biographies

  • Chee Sun Lee, School of Management, University Sains Malaysia

    Chee Sun Lee, is a PhD student in Business Analytics in the School of Management, Universiti Sains Malaysia. He received his Degree and Master Degree in Material Science and Engineering from Universiti Putra Malaysia. He is currently serving as a Supply Chain Engineer in Intel Corporation Malaysia which focuses on Global Supply Chain Integration. His research interests are supply chain performance, supply chain management, Business Analytics and predictive Analysis.

  • Peck Yeng Sharon Cheang, School of Management, ,11800 USM, Penang, Malaysia

    Peck Yeng Sharon Cheang, (Ph.D.) is a lecturer at the School of Management, Universiti Sains Malaysia. She has vast experience in the area of technology transfer and commercialisation management. She obtained her Ph.D. degree in the field of Electrical & Electronics Engineering. Her Ph.D. research has been published in several international journals and has presented at various conferences. Her research interests are in the areas of business analytics, technology/knowledge transfer, entrepreneurship and academic-industry collaborations.


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How to Cite

Lee, C. S., & Cheang , P. Y. S. . (2021). Predictive Analysis in Business Analytics: Application of Decision Tree in Business Decision Making. Advances in Decision Sciences, 26(1), 1-30.