| Bahan Kajian | - Pendahuluan Kecerdasan Buatan, Chaos, dan Nonlinearitas sistem Fisis Bumi
- Pengenalan jenis-jenis algoritma metode kecerdasan buatan atau artificial neural network (ANN) / jaringan syaraf tiruan (JST): (ANN, Fuzzy logic, GA, ACO, SVM, Maksimum entropi, dll)
- Pengenalan dan mengaplikasikan genetic algorithm (GA)
- Pengenalan dan mengaplikasikan ant colony optimization (ACO)
- Pengenalan dan mengaplikasikan Genetic algoritma (GA)
- Pengenalan dan mengaplikasikan Support Vector Machine (SVM)
- Implementasi JST untuk penyelesaian permasalahan peramalan, clustering dan lainnya
- Teori Chaos, Chaos phenomena di Fisika, Chaos di Fluida, Fraktal
- Fenomena Non linearitas, Montecarlo, Statistik Bayesian, Rantai Markov
- Perkembangan ANN terkini: Deep learning (DL) meliputi: Convolutional Neural Network (CNN)
- Recurrent Neural Network (RNN)
- Long Short Term Memory Network (LSTM)
- Bidirectional Long Short Term Memory Network (BiLSTM)
| - Introduction to Artificial Intelligence, Chaos, and Nonlinearity of Earth's Physical Systems
- Introduction to the types of artificial intelligence method algorithms or artificial neural networks (ANN) / artificial neural networks (ANN): (ANN, Fuzzy logic, GA, ACO, SVM, Maximum entropy, etc)
- Introduction and application of genetic algorithms (GA)
- Introduction and application of ant colony optimization (ACO)
- Introduction and application of Genetic Algorithm (GA)
- Introduction and application of Support Vector Machine (SVM)
- Implementation of ANN to solve forecasting, clustering and other problems
- Chaos Theory, Chaos phenomena in Physics, Chaos in Fluids, Fractals
- Non linearity phenomena, Montecarlo, Bayesian statistics, Markov chains
- Recent ANN developments: Deep learning (DL) include: Convolutional Neural Network (CNN)
- Recurrent Neural Network (RNN)
- Long Short Term Memory Network (LSTM)
- Bidirectional Long Short Term Memory Network (BiLSTM)
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| Capaian Pembelajaran Mata Kuliah (CPMK) | - Menguasai metode analisis penggunaan kecerdasan buatan
- Mampu memilih metode kecerdasan buatan yang sesuai untuk menyelesaikan permasalahan sistem fisis bumi
- Mampu mendesain dan mengimplementasikan metode kecerdasan buatan dan digunakan untuk penyelesaian masalah di sistem fisis bumi
- Mampu mengimplementasikan metode deep learning untuk penyelesaian masalah di sistem fisis bumi
| - Mastering analytical methods using artificial intelligence
- Able to choose appropriate artificial intelligence methods to solve problems of the earth's physical system
- Able to design and implement artificial intelligence methods and use them to solve problems in the earth's physical system
- Able to implement deep learning methods for solving problems in the earth's physical system
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