Pengolahan Data Penelitian Lengkap (1 bulan)
Categories: Penelitian
What Will You Learn?
- Pengolahan Data Kuantitatif
- Data Kualitatif
Course Content
Smart PLS
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Landasan kuantitatif dan pengenalan Smart PLS
10:00 -
MATERI, DATA, DAN SOFTWARE CRACK
00:00 -
Bab 2 – Konsep Partial Least Square : Materi
10:00 -
Bab 3 – Mempersiapkan data menginput data [Materi]
10:00 -
Bab 4 – Membuat model PLS-SEM [Materi]
05:00 -
Bab 5 – Evaluasi PLS-SEM Algorithm [Materi]
10:00 -
[Praktik] Bab 5 – Evaluasi PLS-SEM Algorithm
10:00 -
Bab 6 – Evaluasi PLS-SEM Bootstrapping [Materi]
10:00 -
[Praktik] Bab 6 – Evaluasi PLS-SEM Bootstrapping
10:00 -
Bab 7 – Menguji variable intervening [Materi]
10:00 -
[Praktik] Bab 7 – Menguji variable intervening
08:00 -
Bab 8 – Menguji variable moderating [Materi]
02:00 -
[Praktik] Bab 8 – Menguji variable moderating
07:00 -
Bab 9 – Importance-Performance Map Analysis [Materi]
02:00 -
[Praktik] Bab 9 – Importance-Performance Map Analysis
08:00 -
Bab 10 – Higher order construct [Materi]
02:00 -
[Praktik] Bab 10 – Higher order construct
10:00 -
[Praktik] Bab 11 – Multigroup Analysis
09:00 -
Bab 12 – Membuat laporan PLS-SEM [Materi]
00:00 -
[Praktik] Bab 12 – Membuat laporan PLS-SEM
11:00
Eviews
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Software dan File Pendukung
00:00 -
Bab 1 – Pengenalan Software Eviews
00:00 -
Manajemen Data dan Jenis-jenis Data dengan Eviews
05:00 -
Statistik Deskriptif
10:00 -
Uji Regresi Berganda
10:00 -
[Praktik] Manajemen Data
15:00 -
[Praktik] Analysis Regression
15:00 -
Bab 2 – Mengolah Data Panel
00:00 -
Praktik dan Pertanyaan tentang Program AI (Chat GPT dan SpeedWrite)
10:00 -
Analysis Regression Data Panel
10:00 -
Bab 3 – Mengolah Data Time Series dengan AR, MA, ARMA, ARIMA
00:00 -
Jenis Analisis Time Series
15:00 -
Uji Stasioner
15:00 -
Mengolah Data Autoregressive dan ARIMA + Praktik
15:00 -
Uji Normalitas
15:00 -
Uji Multikolinearitas
17:00 -
Uji Heteroskedastisitas
10:00 -
Uji Autokorelasi
10:00
Nvivo – Kualitatif
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Software dan File Pendukung
00:00 -
Bab 1 – Pengantar Penelitian Kualitatif
10:00 -
Perbedaan Penelitian Kualitatif dan Kuantitatif
10:00 -
Fungsi NVivo dalam Analisis Data Kualitatif
10:00 -
Posisi Peneliti dalam Penelitian Kualitatif
10:00 -
Input Data pada NVivo
10:00 -
Bab 2 – Koding
10:00 -
Prinsip melakukan Koding
13:00 -
Tahap-tahap melakukan Koding
15:00 -
Latihan Koding pada NVivo
15:00 -
Tips Melakukan Koding
15:00 -
Proses Generalisasi Data
15:00 -
Bab 3 – Nodes dan Cases
05:00 -
Perbedaan antara Nodes dan Cases
15:00 -
Melakukan Autocade berdasarkan Nama Informan
15:00 -
Membuat Case Classification pada NVivo
15:00 -
Eksplorasi Data menggunakan Fitur Text Search dan Word Tree
15:00 -
Melakukan Koding Tahap 2 dan Tahap 3
15:00 -
Bab 4 – Matrix Coding, Concept Map, dan Project Map
10:00 -
Melakukan Matrix Coding
15:00 -
Interpretasi atas Hasil Matrix Coding
15:00 -
Menggunakan Fitur Concept Map
15:00 -
Menggunakan Fitur Project Map
15:00 -
Memperbaiki Cara Koding
15:00 -
Bab 5 – Penyajian Data dan Visualisasi Data NVivo
17:00 -
Membuat Judul BAB dan Sub BAB
17:00 -
Menarasikan Hasil Interpretasi
15:00 -
Alternatif Penyajian Visualisasi Data NVivo
15:00
Matlab
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Software dan File Pendukung
00:00 -
Bab 1 – Introduction
00:00 -
Basic MATLAB programming
11:00 -
Mathematics and matrix operations
30:00 -
MATLAB scripts and functions
20:00 -
Plotting and data visualization
08:30 -
Bab 2 – Data science
06:00 -
Data Mining
03:00 -
Diagram Venn (data analysis,data mining, machine learning)
03:00 -
Machine Learning
04:00 -
Data Analysis : Metode Simple Additive Weighting (SAW)
04:00 -
Algoritma Metode Simple Additive Weighting (SAW)
03:00 -
Praktik Metode Simple Additive Weighting (SAW)
28:00 -
Machine Learning : K-Nearest Neighbor (KNN)
04:00 -
Algoritma K-Nearest Neighbor (KNN)
04:00 -
Praktik K-Nearest Neighbor (KNN)
04:00 -
Data Analysis : Jaringan Syaraf Tiruan (JST)
04:00 -
Algoritma Jaringan Syaraf Tiruan (JST)
03:00 -
Praktik Jaringan Syaraf Tiruan (JST)
07:00 -
BAB 3 – Citra Digital
15:00 -
Akuisisi Citra Digital
01:00 -
Pengolahan Citra (Image Processing)
03:00 -
Pengenalan Pola (Pattern Recognition)
06:00 -
Computer Vision
15:00 -
Aplikasi Pengolahan Citra : Segmentasi Citra Medis
05:00 -
Aplikasi Pengenalan Pola : Klasifikasi Kualitas Biji Kopi
02:00 -
Deep Learning
03:00 -
Aplikasi Deep Learning : Klasifikasi Jenis Jambu Biji
00:00 -
Transfer Learning
03:00 -
Aplikasi Transfer Learning : Jenis Penyakit Daun Kopi
02:00 -
Praktik Citra Digital
15:00 -
Praktik Analisis Citra : Histogram
05:00 -
Praktik Konversi Citra Grayscale menjadi Biner
05:00 -
Bab 4 – Video Processing
15:00 -
Penerapan Video Processing : Frame Extraction
08:00 -
Praktik Frame Extraction
05:00 -
Penerapan Video Processing : Background Substraction
14:00 -
Praktik Background Substraction
12:00 -
Penerapan Video Processing : Skin Detection
02:00 -
Praktik Skin Detection
06:00 -
Penerapan Video Processing : Lane Detection
03:00 -
Praktik Lane Detection
06:00 -
Audio Processing
05:00 -
Penerapan Audio Processing : Deteksi Kebisingan Motor
04:00 -
Praktik Deteksi Kebisingan Motor
05:00 -
Penerapan Audio Processing : Klasifikasi Suara Anak Tuna Wicara
02:00 -
Praktik Klasifikasi Suara Anak Tuna Wicara
07:00 -
Bab 5 – Persamaan GUIDE dan App Designer
05:00 -
Perbedaan GUIDE dan App Designer
20:00 -
GUIDE
04:00 -
Praktik GUIDE : Grafik Gerak Parabola
25:00 -
Praktik GUIDE Export to MATLAB-file
05:00 -
Praktik GUIDE Migrate to App Designer
03:00 -
Praktik App Designer: Konversi Suhu
15:00 -
Praktik GUIDE : Metode SAW dan Import Export Data
06:00
AMOS
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Software dan File Pendukung
00:00 -
Bab 1 – Introduction to Structural Equation Modeling (SEM)
10:00 -
The Advantages of SEM Compared to OLS
10:00 -
Converting Regression Models into AMOS Graphic
10:00 -
The Concept of Latent Construct in Research
10:00 -
The Minimum Sample Size Required in using SEM
10:00 -
The Variable Terms in SEM using AMOS
10:00 -
Bab 2 – The Models Involved in Structural Equation Modeling [Introduction]
10:00 -
The Role of Theory in Structural Equation Modeling
10:00 -
The Measurement Model for a Construct
10:00 -
The Structural Model in AMOS Graphic and Causal Relationship
10:00 -
The Structural Model: Modeling the Mediator
10:00 -
Bab 3 – Validating the Measurement Model using CFA [Introduction]
10:00 -
Unddimensionalitas
10:00 -
Convergen Validity
10:00 -
Discriminant Validity Fornell & Larcker criterion
10:00 -
Discriminant Validity HTMT ratio
10:00 -
Reliability
10:00 -
Bab 4 – The Measurement Model
00:00 -
Evaluating the Fitness of a Model: The Measurement and Structural Model
10:00 -
The Steps Involved in Validatinga the Measurement Model
10:00 -
Validating the Pooled Measurement Model
10:00 -
Assessing the Validity and Reliability for a Pooled Measurement Model
09:00 -
[Praktik] Model Drawing Using Amos
25:00 -
[Praktik] Model Drawing Using Amos for Model Fit Index
30:00 -
[Praktik] Model Drawing Using Amos Model Struktural
25:00 -
[Praktik] Model Drawing Using Amos direct and indirect efffect
25:00 -
[Praktik] Confirmatory Factor Analisys with second order variable
25:00
Artikel Publikasi Jurnal Scopus
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Writing Approaches & The General Structure Of A Full Article
10:00 -
Title
13:00 -
Authors
07:00 -
Abstract & Keyword
20:00 -
Method
17:00 -
Result
08:00 -
Type Data
04:00 -
Data Presentation
06:00 -
The General Structure Of A Full Article
06:00 -
Discussion
07:00 -
General Rules in Writing Discussion
05:00 -
The Content of Discussion
01:00 -
Contoh Discussion
15:00 -
The General Structure Of A Full Article
01:00 -
Conclusion
05:00 -
References & Citation Style
15:00 -
Acknowledgment
02:00 -
Cover Letter
05:00
SPSS – Data Kuantitatif
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Software dan File Pendukung
00:00 -
Standar Deviation
36:00 -
Konsep Tes Hipotesa
08:00 -
Konsep distribusi normal
46:00 -
Variable
29:00 -
Data transformation in SPSS
40:00 -
Jenis-jenis statistik
30:00 -
Paired sample T test
07:00 -
One-way analysis of variance
37:00 -
Two-way analysis of variance
09:00 -
Reapeted-Measures anova
14:00 -
Non-parametic test
16:00 -
Mann Whitney U test
17:00 -
Kruskal-wallis H tes
14:00 -
Wilcoxon signed rank test
12:00 -
Friedman’s ANOVA
11:00 -
Colleration
19:00 -
Multiple Regression
33:00 -
Logistic Regression
25:00
Join Group Diskusi
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Group Diskusi
00:00