• Statistical Machine Learning (Q)
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    SS234526 - Statistical Machine Learning
    Announcements
    Rencana Pembelajaran Semester (RPS) / Semester Learning Plan
    Announcements
    Week #1 - Introduction to machine learning
    Book: Yu-Wei, David Chiu - Machine Learning with R Cookbook_ Explore over 110 recipes to analyze data and build predictive models with the simple and easy-to-use R code-Packt Publishing (2015)
    Article: Prescriptive analytics - Literature review and research challenges
    Article: 50 Years of Data Science
    Week #1 - Introduction to machine learning (continued)
    Slide-1: Introduction to Statistical Machine Learning
    Slide-2: Data Analytics
    credit-earning program of BDC competition: session 1 (Bagus Sartono) - Teknik Pembelajaran Mesin
    credit-earning program of BDC competition: session 2 (Rangga Pratama) - Clustering in Business
    credit-earning program of BDC competition: session 3 (Dedy Dwi Prastyo) - Unsupervised Machine Learning
    credit-earning program of BDC competition: session 4 (Setia Pramana) - Bioscience Machine Learning
    credit-earning program of BDC competition: session 5 (Sri Astuti Thamrin) - Supervised Learning (part 1)
    credit-earning program of BDC competition: session 6 (Siti Mariyah) - Pemanfaatan Statistical Machine learning pada official statistics
    credit-earning program of BDC competition: session 7a (R Bagus Fajriya Hakim) - Supervised Learning (part 2)
    credit-earning program of BDC competition: session 7b (R Bagus Fajriya Hakim) - SVM
    credit-earning program of BDC competition: session 7c (R Bagus Fajriya Hakim) - ANN
    credit-earning program of BDC competition: session 8 (Yunanto Cahyo Putranto) - Business Intelligence
    Week #2 - Clustering
    slide of the MVA book (Haerdle and Simar) - Clustering
    A Comprehensive Survey of Clustering Algorithms
    MVAclusfood.R
    food.dat
    Unsupervised method - Clustering
    W02-Fuzzy c-means clustering
    W03-DBSCAN
    Week#2: Lecture and Laboratory Exercise
    Laboratory exercise: September 1, 2025, start at 10:00 WIB
    Week #3 - more on Clustering
    CC GENERAL.csv
    Week #3 - Additional material: Clustering in Time Series
    Short review of Clustering
    Clustering in Time Series
    Analisis Cluster untuk Data Time Series
    reference 1 - Time-Series Clustering in R Using the dtwclust Package (the R Journal)
    reference 2 - Comparing time series clustering algorithms in R using dtwclust package
    reference 3 - Computing and Visualizing Dynamic Time Warping Alignments in R - The dtw Package (Journal of Stat Soft)
    reference 4 - TSclust - An R package for time series forecasting (Journal of Stat Soft)
    A Comprehensive Survey of Clustering Algorithms
    Mutual Information-Based Variable Selection on Latent Class Cluster Analysis
    Week #4 - Decision Tree
    SML W11 - Decision Tree
    SML W12 - Tree-based Models
    Week #5 - Random Forest
    Random Forest for Regresion
    slide-6: Supervised learning: Decision Tree and Random Forest (updated)
    Week #6 Support Vector Machine
    slide-3: Supervised Learning: Logistic Regression
    slide-4: Supervised learning: SVM for Classification
    illustration: SVM with polynomial kernel visualization
    Week #7 - Support Vector Regression
    Support Vector Regression - a tutorial (1)
    Support Vector Regression - a tutorial (2)
    slide-5: Support Vector Regression (simulation) updated Sept-2021
    Week #9 - Time Series with NN
    Material MLP in Time Series
    White test
    TErasvirta test
    Material : linearity test
    Week #10 - Neural networks
    Introduction to neural network
    Simple network
    Perceptron
    Multilayer perceptron
    And problem
    neural networks and statistical models (Powell & Duffy)
    NN in SPSS
    NN in R
    Recurrent Neural Networks
    Tugas Neural Network
    Textbook
    Implementation of simple NN using Python
    Convolutional Neural Network
    Tutorial Neural Network dengan Tensorflow
    Week 10 Neural Network
    Materi Week 10
    Week #11 - Backpropagation Neural Net
    Gradient descent
    Backpropagation algorithm
    backpropagation. xlxs
    Materi Week 11
    Week #12-13 - Image Processing
    Quiz Neural Network
    CNN Additional 1
    CNN Additional 2
    Assignment Brief Paper
    Recording CNN
    recording summary image processing
    Week 12
    Week 13
    Weekk #14-15 Text Processing
    Text Processing
    RNN
    Additional
    Forecasting: Principles and Practice
    M Competition
    Practical Time Series Forecasting with R - A Hands-On Guide (2024)
    The Performance of Ramsey Test, White Test and Terasvirta Test in Detecting Nonlinearity - A Simulation Study
    plotXY.R
    Simulation study on ESTAR model
    Design of Experiment to Optimize the Architecture of Deep Learning for Nonlinear Time Series Forecasting
    Pemilihan Arsitektur Terbaik pada Model Deep Learning
    SVR for time series
    nowcasting: predicting the present
    Forecasting with RNN in Intermittent Demand Data
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    Statistical Machine Learning (Q)
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    8. Statistical Machine Learning (Q)
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    Statistical Machine Learning (Q)

    • Teacher: Dedy Dwi Prastyo
    • Teacher: Tintrim Dwi Ary Widhianingsih

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    Sukolilo | Manyar | Tjokroaminoto
    Kampus Institut Teknologi
    Sepuluh Nopember Surabaya
    Phone: 031-5994251-54, 5947274, 5945472
    Fax: 031-5923465, 5947845

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