Mata Kuliah AE5002 - 2026

Kode Mata KuliahAE5002 / 3 SKS
Penyelenggara236 - Teknik Dirgantara / FTMD
KategoriKuliah
Bahasa IndonesiaEnglish
Nama Mata KuliahPerancangan Eksperimen dan Analitika DataDesign of Experiment and Data Analytics
Bahan Kajian
  1. Exploratory Data Analysis
  2. Analysis of Variance (ANOVA)
  3. Blocking
  4. Factorial Design
  5. Computer Experiment
  6. Response Surface Methodologies
  7. Machine Learning: Response Surface Methodologies & Regression
  8. Machine Learning: Classification and Unsupervised Learning
  1. Exploratory Data Analysis
  2. Analysis of Variance (ANOVA)
  3. Blocking
  4. Factorial Design
  5. Computer Experiment
  6. Response Surface Methodologies
  7. Machine Learning: Response Surface Methodologies & Regression
  8. Machine Learning: Classification and Unsupervised Learning
Capaian Pembelajaran Mata Kuliah (CPMK)
  1. Memahami prinsip dasar dan mampu melakukan exploratory data analysis untuk cek karakteristik data
  2. Memahami prinsip-prinsip penting perancangan eksperimen, mencakup ANOVA, Blocking, dan Factorial Design, dan penerapannya.
  3. Memahami prinsip dasar dan teknik-teknik dasar computer experiment
  4. Memahami prinsip machine learning: response surface methodologies dan metode regresi, serta mampu membuat model regresi berdasarkan data
  5. Memahami prinsip machine learning: response surface methodologies dan metode regresi, serta mampu membuat model regresi berdasarkan data
  1. Understand the fundamental principles of data analysis and be able to perform exploratory data analysis (EDA) to examine and characterize datasets.
  2. Understand the fundamental principles of experimental design, including ANOVA, blocking, and factorial design, and their practical applications.
  3. Understand the fundamental principles and basic techniques of computer experiments.
  4. Understand the principles of machine learning, including response surface methodologies and regression techniques, and be able to develop regression models based on data.
  5. Understand the principles of machine learning, including response surface methodologies and regression techniques, and be able to develop regression models based on data.
Metode PembelajaranTatap muka di kelas. Praktikum menggunakan Python/RFace-to-Face Classroom Instruction Hands-on Laboratory Sessions Using Python/R
Modalitas PembelajaranLuring, sinkron, Mandiri dan Kelompok.In-Person Synchronous Learning, Independent Study, and Collaborative Group Learning
Jenis NilaiABCDE
Metode PenilaianUjian Tengah Semester Ujian Akhir Semester Tugas Kuis ProjectMidterm Examination Final Examination Assignments Quizzes Project
Catatan Tambahan