| Kode Mata Kuliah | EL5000 / 3 SKS |
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| Penyelenggara | 232 - Electrical Engineering / STEI |
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| Kategori | Lecture |
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| Bahasa Indonesia | English |
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| Nama Mata Kuliah | Matematika Lanjut | Advanced Mathematics |
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| Bahan Kajian | - Nature dan tujuan penelitian, konsep dan elemen metodologi penelitian
- Penentuan topik penelitian, identifikasi dan perumusan masalah, kebaruan dan/atau nilai inovatif penelitian
- Research question, penentuan hipotesa, perancangan penelitian
- Desain eksperimen, konsep variable bebas dan variable terikat atau metode pemerolahan data lainnya sesuai dengan nature keilmuannya
- Prinsip-prinsip literasi data, artificial intellegence, machine learning dan deep learning
- Pengolahan data, analisis, pembahasan, dan Kesimpulan
- Integritas dan etika dalam riset, proyek, dan publikasi ilmiah
| - Nature and objectives of research, concepts and elements of research methodology
- Determining research topics, identifying and formulating problems, novelty and/or innovative value of research
- Research question, determining hypothesis, research design
- Experimental design, the concept of independent variables and dependent variables or other data processing methods in accordance with the scientific nature
- Principles of data literacy, artificial intelligence, machine learning, and deep learning
- Data processing, analysis, discussion and conclusions
- Integrity and ethics in research, projects, and academic publications
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| Capaian Pembelajaran Mata Kuliah (CPMK) | - Mahasiswa memahami nature dan tujuan penelitian, konsep dan elemen metodologi penelitian
- Mahasiswa mampu menentukan topik penelitian, mengidentifikasi dan merumuskan masalah, menentukan kebaruan dan/atau nilai inovatif penelitian
- Mahasiswa mampu menentukan research question, hipotesa, dan merancang penelitian untuk tugas akhir magisternya
- Mahasiswa mampu merancang eksperimen atau metode pemerolehan data lainnya sesuai dengan nature keilmuannya dan mampu memahami prinsip-prinsip lierasi data, artificial intellegence, machine learning dan deep learning
- Mahasiswa mampu mengolah data, menganalisis, dan melakukan pembahasan serta Kesimpulan dari hasil penelitian yang diperoleh
- Mampu menghayati, menghormati, dan menegakkan integritas dan etika dalam melakukan riset, proyek, dan publikasi ilmiah
| - Students understand the nature and purpose of research, as well as the concepts and elements of research methodology
- Students are capable of determining research topics, identifying and formulating problems, and determining the novelty and/or innovative value of the research.
- Students are capable of determining research questions, hypotheses, and designing research for their master's thesis
- Students are capable of designing experiments or other data acquisition methods according to the nature of their scientific field and capable of understanding the principles of data literacy, artificial intelligence, machine learning, and deep learning
- Students are capable of processing data, analyzing it, and conducting
- Capable of appreciating, respecting, and upholding integrity and ethics in conducting research, projects, and academic publications
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| Metode Pembelajaran | Kuliah, diskusi, kerja mandiri | Lecture, Discussion, Independent Work |
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| Modalitas Pembelajaran | Luring Sinkron, Daring Asinkron | Synchronous Offline, Asynchronous Online |
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| Jenis Nilai | ABCDE |
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| Metode Penilaian | Tugas, Tugas Besar, Presentasi | Assignments, Project, Presentation |
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| Catatan Tambahan | | |
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