50 students

Data Mining adalah kegiatan yang meliputi pengumpulan, pemakaian data historis untuk menemukan keteraturan, pola dan hubungan dalam set data berukuran besar. Kegunaan data mining adalah untuk menspesifikasikan pola yang harus ditemukan dalam tugas data mining. Kehadiran data mining dilatarbelakangi dengan problema data explosion yang dialami akhir-akhir ini dimana banyak organisasi telah mengumpulkan data sekian tahun lamanya (data pembelian, data penjualan, data nasabah, data transaksi dsb.)

Pembahasan materi pada Training Data Mining Applications Using Rapidminer ini fokus pada pemanfaatan data mining dalam dunia nyata. Pada training ini, anda akan mempelajari penerapan data mining menggunakansoftware Rapid Miner. Anda akan mendapatkan banyak studi kasus penerapan Data Mining. Diharapkan setelah mengikuti training ini, anda siap menghadapi tantangan kasus-kasus pada penerapan Data Mining pada kehidupan nyata.

CONTENT

1. Introduction to Data Mining and RapidMiner

1.1. Introduction

1.2. Getting Used to RapidMiner

2. Basic Classification Use Cases for Credit Approval and in Education

2.1. k-Nearest Neighbor Classification I

2.2. k-Nearest Neighbor Classification II

2.3. Naive Bayes Classification I

2.4. Naive Bayes Classificaton II

3. Marketing, Cross-Selling, and Recommender System Use Cases

3.1. Affinity-Based Marketing

3.2. Basic Association Rule Mining in RapidMiner

3.3. Constructing Recommender Systems in RapidMiner

3.4. Recommender System for Selection of the Right Study Program for Higher Education Students

4. Clustering in Medical and Educational Domains

4.1. Visualising Clustering Validity Measures

4.2. Grouping Higher Education Students with RapidMiner

5. Text Mining: Spam Detection, Language Detection, and Customer Feedback Analysis

5.1. Detecting Text Message Spam

5.2. Robust Language Identification with RapidMiner: A Text Mining Use Case

5.3. Text Mining with RapidMiner

6. Feature Selection and Classification in Astroparticle Physics and in Medical Domains

6.1. Application of RapidMiner in Neutrino Astronomy

6.2. Medical Data Mining

7. Molecular Structure- and Property-Activity Relationship Modeling in Biochemistry and Medicine

7.1. Using PaDEL to Calculate Molecular Properties and Chemoinformatic Models

7.2. Chemoinformatics: Structure- and Property-activity Relationship Development

8. Image Mining: Feature Extraction, Segmentation, and Classification

8.1. Image Mining Extension for RapidMiner (Introductory)

8.2. Image Mining Extension for RapidMiner (Advanced)

9. Anomaly Detection, Instance Selection, and Prototype Construction

9.1. Instance Selection in RapidMiner

9.2. Anomaly Detection

10. Meta-Learning, Automated Learner Selection, Feature Selection, and Parameter Optimization

10.1. Using RapidMiner for Research: Experimental Evaluation of Learners

Data Mining Using RapidMiner
  • Pengenalan Data Mining / Data Sains dan RapidMiner
    No items in this section
  • Basic Classification Use Cases for Credit Approval and in Education
    No items in this section
  • Marketing, Cross-Selling, and Recommender System Use Cases
    No items in this section

Instructor

Rp2,500,000.00 Rp2,400,000.00

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