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 courseThis 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
■※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
■※Main reference books/materials (Textbooks and References) (Textbooks comply with the concept of intellectual property rights and are not illegally photocopied) (limited to 4000 words)
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 categorizing 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
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| Reading Assignment Reading Assignment 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 assignmentWeekly assignment weekly assignment |
35 | Students are working on some data set to utilize the KDD process |
| Case study assignmentCase study assignment case study assignment |
50 | Students are working on case studies to apply relevant theories, knowledge, and technical methods. Students are writing their academic report. |
