Preface
About the Writer
Bakti Siregar, M.Sc., CDSS works as a Lecturer at the ITSB Data Science Program. He earned his Master’s degree from the Department of Applied Mathematics at National Sun Yat Sen University, Taiwan. In addition to teaching, Bakti also works as a Freelance Data Scientist for leading companies such as JNE, Samora Group, Pertamina, and PT. Green City Traffic.
He has a strong enthusiasm for projects (and teaching) in the fields of Big Data Analytics, Machine Learning, Optimization, and Time Series Analysis, particularly in finance and investment. His core expertise lies in statistical programming languages such as R Studio and Python. He is also experienced in implementing database systems like MySQL/NoSQL for data management and is proficient in using Big Data tools such as Spark and Hadoop.
Some of his projects can be viewed here: Rpubs, Github, Website, and Kaggle
Acknowledgments
Linear Algebra is more than just theory, it’s a powerful toolkit for solving real challenges in mining engineering. From handling large systems of equations to applying eigenvalues in stability analysis, the concepts covered here are designed to connect mathematics directly with mining practice. This book introduces the essentials: matrices, determinants, inverses, factorizations, vector spaces, inner products, orthogonality, linear transformations, and eigenvalues—always with a focus on how they translate into real mining applications.
We thank all readers and learners who bring curiosity and fresh perspectives. Your questions and insights keep this journey alive. Our hope is that this material not only strengthens your foundation in Linear Algebra but also inspires you to use it as a driver of innovation, safety, and efficiency in mining engineering..
Feedback & Suggestions
Your feedback is invaluable in helping us refine and improve this book. We encourage readers to share their thoughts on the clarity, structure, and practical relevance of the material. Suggestions for expanding discussions—whether on matrices and systems of linear equations, determinants and matrix factorizations, vector spaces and orthogonality, or linear transformations and eigenvalues—are highly appreciated.
With your contributions, we aim to make this book a comprehensive and practice-oriented resource on Linear Algebra for Mining Engineering. Thank you for your engagement and support in shaping this learning journey.
For feedback and suggestions, please contact:
- siregarbakti@gmail.com
- siregarbakti@itsb.ac.id
- dsciencelabs@outlook.com