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Konsep Aplikasi Data Mining
Eka Yuniar, S.Kom., MMSI
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SAP 1. Menjelaskan Definisi KDD 2. KDD Life Cycle 3. Data Warehouse 4. OLAP 5. Macam-macam OLAP 6. Arsitektur KDD 7. Arsitektur OLAP
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Apa itu KDD??
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Knowledge Discovery in Database
Definition ”the non-trivial extraction of implicit, previously unknown and potentially useful knowledge from data” (Fall, 2003) Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. (Romi, 2010)
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Mengapa Menggunakan KDD ??
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Mengapa menggunakan KDD?
Untuk mencari trend dan korelasi/hubungan/relation dalam data base dan dapat membantu untuk mencari informasi. Dengan tujuan : Efektif/ to more effective • menghemat waktu/ to save time • menguntungkan/to make more money • Kualitas produk/to improve product quality • to etc.
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Application Marketing Market segmentation Clasification custumer
Predict future sales Product Maintenance Define product interest from customer
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Human Resource Management
Define an employee compensation Define an employee punishment Finance Detect fraudulent use of credit cards Etc…
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KDD Life Cycle
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OnLine Analytical Processing (OLAP)
”the dynamic synthesis, analysis, and consolidation of large volumes of multi-dimensional data” Focuses on multi-dimensional relationships among existing data records
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Olap Vs. SQL OLAP : Menambahkan Analisis dalam Tools
SQL : eksekusi roll-up, drill-down, slice, dice, pivot dari DW
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OLAP differs from data mining
– OLAP tools provide quantitative analysis of multi-dimensional data relationships – Data mining tools create and evaluate a set of possible problem solutions (and rank them) • Ex: Propose 3 marketing strategies and order them based on marketing cost and likely sales income
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Architectures for OLAP
Three system architectures are used for OLAP – Relational OLAP (ROLAP) – Multi-dimensional OLAP (MOLAP) – Managed Query Environment (MQE)
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ROLAP
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MOLAP
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MQE
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Cycle of SQL
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KDD Architecture
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