Mata Kuliah IF4041 - 2024

Kode Mata KuliahIF4041 / 3 SKS
Penyelenggara135 - Teknik Informatika / STEI
KategoriKuliah
Bahasa IndonesiaEnglish
Nama Mata KuliahPenambangan DataData Mining
Bahan Kajian
  1. DS-DG-1. Data acquisition
  2. DS-DG-2. Information extraction
  3. DS-DG-3. Working with various types of data
  4. DS-DG-4. Data integration
  5. DS-DG-5. Data reduction and compression
  6. DS-DG-6. Data transformation
  7. DS-DG-7. Data cleaning
  8. DS-DM-1. Proximity measurement
  9. DS-DM-2. Data preparation
  10. DS-DM-3. Information extraction
  11. DS-DM-4. Cluster analysis
  12. DS-DM-5. Classification and regression
  13. DS-DM-6. Pattern mining
  14. DS-DM-7. Outlier detection
  15. DS-DM-8. Time series data
  16. DS-DM-9. Mining web data
  17. DS-DM-10. Information retrieval
  1. DS-DG-1. Data acquisition
  2. DS-DG-2. Information extraction
  3. DS-DG-3. Working with various types of data
  4. DS-DG-4. Data integration
  5. DS-DG-5. Data reduction and compression
  6. DS-DG-6. Data transformation
  7. DS-DG-7. Data cleaning
  8. DS-DM-1. Proximity measurement
  9. DS-DM-2. Data preparation
  10. DS-DM-3. Information extraction
  11. DS-DM-4. Cluster analysis
  12. DS-DM-5. Classification and regression
  13. DS-DM-6. Pattern mining
  14. DS-DM-7. Outlier detection
  15. DS-DM-8. Time series data
  16. DS-DM-9. Mining web data
  17. DS-DM-10. Information retrieval
Capaian Pembelajaran Mata Kuliah (CPMK)
  1. CPMK1. Memformulasi solusi dari persoalan data science dengan proses data mining.
  2. CPMK2. Menerapkan dasar-dasar exploratory analysis untuk identifikasi data abnormali, termasuk identifikasi data bias.
  3. CPMK3. Menentukan beberapa algoritma yang cocok/tepat untuk suatu persoalan, termasuk juga analisa tentang kelebihan dan kekurangan.
  4. CPMK4. Menjelaskan model regularization
  1. Formulate solutions to data science problems using the data mining process
  2. Apply exploratory analysis foundations to identify data abnormalities, including bias identification
  3. Determine several algorithms suitable for a problem, including analyzing strengths and weaknesses
  4. Explain regularization models
Metode PembelajaranKuliah, Presentasi, Diskusi, Case study, Problem-based Learning, Studi literatur, Kerja kelompok, Project-based Learning (PBL)Lectures, Presentations, Discussions, Case Studies, Problem-Based Learning, Literature Review, Group Work, Project-Based Learning (PBL)
Modalitas PembelajaranDaring//Luring Sinkron/Asinkron Mandiri/KelompokOffline (Luring); Synchronous; Independent/Group
Jenis NilaiABCDE
Metode PenilaianUTS, UAS, Kuis, TugasMid-term exams, final exams, quizzes, assignments
Catatan Tambahan