Mata Kuliah MS5100 - 2026

Kode Mata KuliahMS5100 / 3 SKS
Penyelenggara231 - Mechanical Engineering / FTMD
KategoriLecture
Bahasa IndonesiaEnglish
Nama Mata KuliahPerancangan Eksperimen dan Analitika DataDesign of Experiment and Data Analytics
Bahan Kajian
  1. Analisis Data Eksploratif
  2. Analisis Varians (ANOVA)
  3. Blocking
  4. Desain Faktorial
  5. Eksperimen Komputasi
  6. Metodologi Permukaan Respons
  7. Pembelajaran Mesin: Metodologi Permukaan Respons & Regresi Linear
  8. Pembelajaran Mesin: Klasifikasi
  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
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 basic principles and be able to carry out exploratory data analysis to examine data characteristics
  2. Understand the important principles of experimental design, including ANOVA, Blocking, Factorial Design, and their applications
  3. Understand the basic principles and basic techniques of computer experiments
  4. Understand machine learning principles: response surface methodologies and regression methods, and be able to create regression models based on data
  5. Understand machine learning principles: response surface methodologies and regression methods, and be able to create regression models based on data
Metode PembelajaranTatap muka di kelas. Praktikum menggunakan Python/RClassroom lectures Practicum using Python/R
Modalitas PembelajaranLuring, sinkron, Mandiri dan Kelompok.Offline, synchronous, autonomous and group-based learning.
Jenis NilaiABCDE
Metode PenilaianUjian Tengah Semester Ujian Akhir Semester Tugas Kuis ProjectMidterm Examination, Final Examination, Assignments
Catatan Tambahan