Page 5 - E Modul Data Analytics _Neat

Data Analytics

3.4.2 Untstructured Data (Data Tidak Terstruktur) ....................................................... 36
KEGIATAN PEMBELAJARAN 4 ................................................................................................... 37

Mencari Pattern dan Insight dari Data...................................................................................... 37
4.1 Menganalisis Kebutuhan ( Requiremets organization) .......................................... 38
4.1.1 Business Understanding ..................................................................................... 39

4.1.2 Data Understanding ............................................................................................. 40
4.2 Mengembangkan model ............................................................................................. 41
4.2.1 Data Preparation .................................................................................................. 41

4.2.2 Modelling ............................................................................................................... 42
4.2.3 Evaluation .............................................................................................................. 42

4.2.4 Deployment ........................................................................................................... 42
KEGIATAN PEMBELAJARAN 5 ................................................................................................... 43
5.1 Fenomena Model Data dari Data ................................................................................. 44

5.1.1 Record data ........................................................................................................... 46
5.2 Prediksi dari Data ............................................................................................................ 49
5.3 Konsep Data Mining ........................................................................................................ 51

5.3.1 Seleksi Data .......................................................................................................... 52
5.3.2 Pre-processing/Cleaning (Pemilihan data)....................................................... 52
5.3.3 Transformasi ......................................................................................................... 53

5.3.4 Data mining ........................................................................................................... 53
5.3.5 Interpretasi/Evaluasi ............................................................................................ 53

KEGIATAN PEMBELAJARAN 6 ................................................................................................... 54
6.1 Tujuan Metode Regresi .................................................................................................. 55
6.2 Regresi linear dan non-linear..................................................................................... 55

6.2.1 Regresi Linear........................................................................................................... 55
6.2.2 Regresi Non- Linear ............................................................................................. 57
6.3 Least Square Regression, Logistic Regression ...................................................... 58

6.3.1 Least Square Regression (Kuadrat Terkecil regresi) ..................................... 58
6.3.2 Logistic Regression .............................................................................................. 59
6.4 Aplikasi Regresi ( Studi Kasus) ................................................................................. 61

6.5 Penggunaan Software untuk pengelolaan model Regresi. ...................................... 66
KEGIATAN PEMBELAJARAN 7 .............................................................................................. 71
Konsep Dasar Metoda Data Mining: Metoda Classification and Prediction ..................... 71

7.1 Definisi Metode klasifikasi .............................................................................................. 72

v