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Course Description
The Artificial Intelligence course discusses the problem solving process in artificial machine intelligence, namely searching, reasoning, planning, learning, and method application. This content includes an introduction to Artificial Intelligence, expert systems, machine learning methods, data mining methods, Fuzzy Logic, and Neural Network optimization methods. This learning also discusses the advantages and disadvantages of each method for solving a problem, evolutionary computation, hybrid intelligent systems and how to implement AI and choose the most appropriate techniques and methods for various problems. Lectures are carried out proportionally between theory and practice (assignments), discussions of theory are carried out in general, philosophical motivation, differences between existing techniques, methods, modeling and applications.
Program Objectives (PO)
- Mahasiswa mampu mengenal dan memahami Artificial intelligence (Kecerdasan Buatan)
- Mahasiswa mampu memahami mekanisme pemecahan masalah yang paling umum dalam suatu Artificial intelligence (Kecerdasan Buatan)
- Mahasiswa mampu merepresentasikan permasalahan ke dalam basis pengetahuan menggunakan logic atau Bahasa formal
- Mahasiswa mampu menjelaskan studi kasus: mengubah masalah ke dalam ruang masalah operator yang digunakan
- Mahasiswa mampu menjelaskan metode-metode pencarian
- Mahasiswa mampu memahami tentang Blind Search/Uninformed Search dan Informed Search
- Mahasiswa mampu memahami tentang Reasoning (penalaran) Propositional Logic dan First Order Logic
- Mahasiswa mampu memahami tentang fuzzy sistem
- Mahasiswa mampu memahami tentang learning (penalaran) Artificial Intelligence dengan decision tree Bayes dan jaringan syaraf tiruan
- Mahasiswa mampu memahami pemodelan Artificial Intelligence (AI) dengan metode optimisasi dengan machine learning, data mining, dan jaringan syaraf tiruan
- Mahasiswa mampu mengaplikasikan dengan AI
Aktifitas Pembelajaran
-
Pertemuan 1 Dan mampu memahami, menjelaskan dan dapat memberikan gambaran umum atau memberikan pengantar umum mengenai Artificial Intellegence (AI) dan teknik serta metode Artificial Intellegence -
Pertemuan 2 Dan menjelaskan searching (Pencarian) mengenai ruang masalah, sistem produksi -
Pertemuan 3 Tentang blind search/Uniformed search -
Pertemuan 4 Tentang blind search/Uniformed search -
Pertemuan 5 Proposional Logic dan First Order Logic -
Pertemuan 6 -
Pertemuan 7 Pengembangan metode Fuzzy dengan Fuzzy decision making -
Pertemuan 8 -
Pertemuan 9 Planning (perencanaan) dengan dunia balok, Goal Stack planning dan constraint posting -
Pertemuan 10 -
Pertemuan 11 Pemodelan optimasi Naïve Bayes dan Algoritma genetik -
Pertemuan 12 Machine learning model, dan data mining -
Pertemuan 13 Model sel syaraf untuk pemodelan menggunakan jaringan syaraf tiruan, layer perceptron, back propagation, learning vector -
Pertemuan 14 Hopfield neural network, annealid neural network, deep learning -
Pertemuan 15 Dan mengimplementasikan aplikasi AI (Artificial Intellegence) dengan berbasis IoT -
Pertemuan 16 Ujian Akhir Semester (Semua Materi Perkuliahan)
References
Lecturer
Difficult Things About Education.
$75$10
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