Kode Mata KuliahMS5091 / 4 SKS
Penyelenggara231 - Teknik Mesin / FTMD
KategoriKuliah
Bahasa IndonesiaEnglish
Nama Mata KuliahMatematika Lanjut AAdvanced Mathematics A
Bahan Kajian
  1. Ruang Fungsi
  2. Transformasi Linear pada Ruang Fungsi
  3. Pendekatan Geometris untuk Dinamika Nonlinear
  4. Persamaan Diferensial Parsial (Metode Karakteristik)
  5. Ruang Linear dan Transformasi Linear
  6. Sistem Persamaan Linear
  1. Function Space
  2. Linear Transformation on Function Spaces
  3. Geometrical Approach to Nonlinear Dynamics
  4. Partial Differential Equations (Method of Characteristics)
  5. Linear Space and Linear Transformation
  6. System of Linear Equations
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
  6. Memahami dan dapat menggunakan konsep ruang linear dan transformasi linear pada ruang fungsi
  7. Memahami penggunaan persamaan differensial dalam dunia sains dan rekayasa.
  8. Memahami persamaan differensial biasa menggunakan pendekatan geometris/kualitatif.
  9. Memahami prinsip kerja dan dapat menggunakan method of characteristics untuk penyelesaian persamaan differensial parsial.
  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, and 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
  6. Understand and be able to use the concept of linear space and linear transformations in function spaces
  7. Understand the use of differential equations in the world of science and engineering.
  8. Understand ordinary differential equations using a geometric/qualitative approach.
  9. Understand working principles and be able to use the method of characteristics to solve partial differential equations.
Metode PembelajaranTatap muka di kelas. Tutorial materi kuliah.
Modalitas PembelajaranLuring, sinkron, mandiri.
Jenis NilaiABCDE
Metode PenilaianUjian Tengah Semester. Ujian Akhir Semester. Tugas.
Catatan Tambahan