Ilmu Data: Perbedaan antara revisi
←Membuat halaman berisi '📊 Konsep Utama dalam Ilmu Data Tahap 1: Pengambilan, Penyimpanan, dan Pembersihan Data Big Data Basis Data Relasional NoSQL Data Warehouse Data Lake ETL (Extract, Transform, Load) atau ELT Data Wrangling Data Cleansing (Pembersihan Data) Penanganan Data Hilang Deteksi Outlier Tahap 2: Analisis dan Eksplorasi Data Statistika Deskriptif St...' |
Tidak ada ringkasan suntingan |
||
| Baris 1: | Baris 1: | ||
📊 Konsep Utama dalam [[Ilmu Data]] | 📊 Konsep Utama dalam [[Ilmu Data]] | ||
Tahap 1 | Tahap 1 [[Pengambilan Data|Pengambilan, Penyimpanan, dan Pembersihan Data]] | ||
[[Big Data]] | # [[Big Data]] | ||
[[Database|Basis Data Relasional]] | # [[Database|Basis Data Relasional]] | ||
[[NoSQL]] | # [[NoSQL]] | ||
[[Data Warehouse]] | # [[Data Warehouse]] | ||
[[Data Lake]] | # [[Data Lake]] | ||
[[ETL (Extract, Transform, Load)]] atau [[ELT]] | # [[ETL (Extract, Transform, Load)]] atau [[ELT]] | ||
[[Data Wrangling]] | # [[Data Wrangling]] | ||
[[Data Cleansing]] (Pembersihan Data) | # [[Data Cleansing]] (Pembersihan Data) | ||
[[Missing Data|Penanganan Data Hilang]] | # [[Missing Data|Penanganan Data Hilang]] | ||
[[Outlier|Deteksi Outlier]] | # [[Outlier|Deteksi Outlier]] | ||
Tahap 2 | Tahap 2 [[Eksplorasi Data|Analisis dan Eksplorasi Data]] | ||
[[Statistika Deskriptif]] | # [[Statistika Deskriptif]] | ||
[[Statistika Inferensial]] | # [[Statistika Inferensial]] | ||
[[Visualisasi Data]] | # [[Visualisasi Data]] | ||
[[Variabel]] dan [[Distribusi Probabilitas]] | # [[Variabel]] dan [[Distribusi Probabilitas]] | ||
[[Uji Hipotesis]] | # [[Uji Hipotesis]] | ||
[[Regresi Linier]] | # [[Regresi Linier]] | ||
[[Korelasi]] | # [[Korelasi]] | ||
[[Analisis Runtun Waktu|Analisis Time Series]] | # [[Analisis Runtun Waktu|Analisis Time Series]] | ||
[[A/B Testing]] | # [[A/B Testing]] | ||
Tahap 3 | Tahap 3 [[Pembelajaran Mesin|Pemodelan (Machine Learning)]] | ||
[[Pembelajaran Mesin (Machine Learning)]] | # [[Pembelajaran Mesin (Machine Learning)]] | ||
[[Kecerdasan Buatan (Artificial Intelligence)]] | # [[Kecerdasan Buatan (Artificial Intelligence)]] | ||
[[Pembelajaran Terawasi|Supervised Learning]] (Klasifikasi, Regresi) | # [[Pembelajaran Terawasi|Supervised Learning]] (Klasifikasi, Regresi) | ||
[[Pembelajaran Tak Terawasi|Unsupervised Learning]] (Clustering, Pengurangan Dimensi) | # [[Pembelajaran Tak Terawasi|Unsupervised Learning]] (Clustering, Pengurangan Dimensi) | ||
[[Pembelajaran Diperkuat|Reinforcement Learning]] | # [[Pembelajaran Diperkuat|Reinforcement Learning]] | ||
[[Deep Learning]] | # [[Deep Learning]] | ||
[[Jaringan Saraf Tiruan|Jaringan Saraf Tiruan (Neural Network)]] | # [[Jaringan Saraf Tiruan|Jaringan Saraf Tiruan (Neural Network)]] | ||
[[Validasi Silang|Cross-Validation]] | # [[Validasi Silang|Cross-Validation]] | ||
[[Overfitting]] dan [[Underfitting]] | # [[Overfitting]] dan [[Underfitting]] | ||
[[Fitur Engineering|Rekayasa Fitur (Feature Engineering)]] | # [[Fitur Engineering|Rekayasa Fitur (Feature Engineering)]] | ||
[[Algoritma Klasifikasi|Algoritma: K-Nearest Neighbors (KNN)]] | # [[Algoritma Klasifikasi|Algoritma: K-Nearest Neighbors (KNN)]] | ||
[[Algoritma Klasifikasi|Algoritma: Pohon Keputusan (Decision Tree)]] | # [[Algoritma Klasifikasi|Algoritma: Pohon Keputusan (Decision Tree)]] | ||
[[Algoritma Klasifikasi|Algoritma: Support Vector Machine (SVM)]] | # [[Algoritma Klasifikasi|Algoritma: Support Vector Machine (SVM)]] | ||
[[Algoritma Klasifikasi|Algoritma: Naive Bayes]] | # [[Algoritma Klasifikasi|Algoritma: Naive Bayes]] | ||
[[Algoritma Klasifikasi|Algoritma: Random Forest]] | # [[Algoritma Klasifikasi|Algoritma: Random Forest]] | ||
[[Algoritma Clustering|Algoritma: K-Means Clustering]] | # [[Algoritma Clustering|Algoritma: K-Means Clustering]] | ||
Tahap 4 | Tahap 4 [[Aplikasi Data Science|Penyebaran dan Domain Khusus]] | ||
[[Natural Language Processing (NLP)]] (Pemrosesan Bahasa Alami) | # [[Natural Language Processing (NLP)]] (Pemrosesan Bahasa Alami) | ||
[[Computer Vision]] | # [[Computer Vision]] | ||
[[Model Deployment]] (Penyebaran Model) | # [[Model Deployment]] (Penyebaran Model) | ||
[[Dashboard Interaktif]] | # [[Dashboard Interaktif]] | ||
[[Big Data Analytics]] | # [[Big Data Analytics]] | ||
[[Etika Data]] dan [[Bias Algoritma]] | # [[Etika Data]] dan [[Bias Algoritma]] | ||
[[Keamanan Data]] | # [[Keamanan Data]] | ||
[[Business Intelligence (BI)]] | # [[Business Intelligence (BI)]] | ||
Revisi per 8 November 2025 23.30
📊 Konsep Utama dalam Ilmu Data Tahap 1 Pengambilan, Penyimpanan, dan Pembersihan Data
- Big Data
- Basis Data Relasional
- NoSQL
- Data Warehouse
- Data Lake
- ETL (Extract, Transform, Load) atau ELT
- Data Wrangling
- Data Cleansing (Pembersihan Data)
- Penanganan Data Hilang
- Deteksi Outlier
Tahap 2 Analisis dan Eksplorasi Data
- Statistika Deskriptif
- Statistika Inferensial
- Visualisasi Data
- Variabel dan Distribusi Probabilitas
- Uji Hipotesis
- Regresi Linier
- Korelasi
- Analisis Time Series
- A/B Testing
Tahap 3 Pemodelan (Machine Learning)
- Pembelajaran Mesin (Machine Learning)
- Kecerdasan Buatan (Artificial Intelligence)
- Supervised Learning (Klasifikasi, Regresi)
- Unsupervised Learning (Clustering, Pengurangan Dimensi)
- Reinforcement Learning
- Deep Learning
- Jaringan Saraf Tiruan (Neural Network)
- Cross-Validation
- Overfitting dan Underfitting
- Rekayasa Fitur (Feature Engineering)
- Algoritma: K-Nearest Neighbors (KNN)
- Algoritma: Pohon Keputusan (Decision Tree)
- Algoritma: Support Vector Machine (SVM)
- Algoritma: Naive Bayes
- Algoritma: Random Forest
- Algoritma: K-Means Clustering
Tahap 4 Penyebaran dan Domain Khusus
- Natural Language Processing (NLP) (Pemrosesan Bahasa Alami)
- Computer Vision
- Model Deployment (Penyebaran Model)
- Dashboard Interaktif
- Big Data Analytics
- Etika Data dan Bias Algoritma
- Keamanan Data
- Business Intelligence (BI)