113年第1學期-5570 Data Mining and Business Intelligence 課程資訊

評分方式

評分項目	配分比例	說明
Reading Assignment	15	Students are studying selected international journal articles to follow state-of-the-art discussion in the area data mining and its application in Industrial Engineering
Weekly assignment	35	Students are working on some data set to utilize the KDD process
Case study assignment	50	Students are working on case studies to apply relevant theories, knowledge, and technical methods. Students are writing their academic report.

教育目標

This course covers several topics includes: 1. Introduction to Knowledge Data Discovery (KDD) 2. Data Acquisition 3. Pre-Processing Data 4. Data Visualization 5. Predictive Technique using Linear Regression 6. Classification Techniques using Logistics Regression, Linear Discriminant Analysis and Support Vector Machine 7. Clustering Techniques using K Means and Hierarchical Clustering 8. Association Rule Technique for special implementation in the retail sector 9. Random Forest Techniques and Introduction to Machine Learning (Neural Network Concept) 10. Text Mining *R software or Python will be used in this course

基本資料

選修課，學分數：3-0
上課時間：一/6,7,8[IEⅡ102]
修課班級：工工碩博1,2
修課年級：1年級以上
選課備註：英語授課

參考書目

■※主要參考書籍/資料 (Textbooks and References) (教科書遵守智慧財產權觀念不得非法影印) (限4000字)
Textbooks:
[1]Larose, D.T. & Larose, C.D. Discovering Knowledge in Data: An Introduction to Data Mining. John Wiley & Sons.
[2]Evans, J.R. Business Analytics Global Edition 3rd edition, Pearson Education Limited 2021.
Articles:
[3] Sutrilastyo, and Astanti, Ririn Diar. "Supervised multilabel classification techniques for categorising customer requirements during the conceptual phase in the new product development" .Engineering Management in Production and Services, vol.16, no.1, 2024, pp.31-47. https://doi.org/10.2478/emj-2024-0003
[4] Raja, Anton Merl Lumban; Ai, The Jin, and Astanti, Ririn Diar. “A Clustering Classification of Spare Parts for Improving Inventory Policies”. Conference Series Materials Science and Engineering 114(1):012075. DOI: 10.1088/1757-899X/114/1/012075
[5] Astanti, Ririn Diar., Sutanto, Ivana Carissa. and Ai, The Jin (2022), "Complaint management model of manufacturing products using text mining and potential failure identification". The TQM Journal, vol. 34 no. 6, pp. 2056-2068. https://doi.org/10.1108/TQM-05-2021-0145
[6] Sutrilastyo, and Astanti, Ririn Diar. (2021). “Lexicon-based Sentiment Analysis for Product Design and Development.” International Journal of Industrial Engineering and Engineering Management, vol.3 no.1,pp. 27–31. https://doi.org/10.24002/ijieem.v3i1.4351
[7] Astanti, Ririn Diar and Switasarra, Adelia Veneska,. “Text Mining Based Process Identification and Business Process
Mapping from Job Description Documents”. Management and Production Engineering Review, vol. 15, no.1, pp. 63–75 DOI: 10.24425/mper.2024.149990
[8] Lecturer’s module