Page 5 - E Modul Data Analytics
P. 5

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
   1   2   3   4   5   6   7   8   9   10