Perbandingan pemodelan matematika untuk strategi blackjack menggunakan simulasi monte carlo dan naive bayes = Mathematical modeling comparison for blackjack strategy using monte carlo simulation and naive bayes

Louise, Danielle (2022) Perbandingan pemodelan matematika untuk strategi blackjack menggunakan simulasi monte carlo dan naive bayes = Mathematical modeling comparison for blackjack strategy using monte carlo simulation and naive bayes. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Blackjack merupakan salah satu permainan kasino yang unik karena permainan tersebut memungkinkan player untuk menang. Blackjack sendiri memberi pemain banyak opsi aksi yang bisa dipilih untuk memenangkan permainan ini. Player dapat belajar bagaimana cara bermain dengan strategi yang menguntungkan, yang telah dibuat oleh Edward O. Thorp, atau menggunakan intuisi untuk memilih langkah berikutnya. Namun, dengan kapasitas waktu dan informasi yang diberikan, tidak menutup kemungkinan ada langkah yang lebih optimal dibandingkan dengan pilihan player. Dengan perkembangan ilmu teknologi komputer dan ide dari Arthur L. Samuel untuk menyelesaikan permainan melalui program, terdapat berbagai macam metode dan algoritma yang dapat digunakan untuk mengolah dan mengoptimalkan data, salah satunya adalah dengan menggunakan machine learning. Salah satu algoritma yang sering digunakan untuk memprediksi dan klasifikasi data adalah Naive Bayes, dikarenakan algoritma tersebut cukup akurat dan efisien. Dalam penelitian ini, akan dibandingkan metode Monte Carlo dan Naive Bayes. Peluang dari masing-masing metode dihitung sedemikian rupa sehingga didapat strategi. Strategi yang dibentuk dengan simulasi Monte Carlo cukup akurat dibandingkan dengan strategi optimal menurut Thorp, namun prediksi strategi dari Naive Bayes hanya akurat saat player stay. Hal ini dikarenakan model Naive Bayes tidak dibuat berdasarkan aturan dan cara bermain blackjack, tetapi berdasarkan data. / Blackjack is one of the most unique casino games because it gives players a chance to win. In blackjack, players are given many options to choose an action in order to win. Players can learn how to play the optimal strategy of blackjack, which was made by Edward O. Thorp, or they can use their intuition to choose the next step. However, with the lack of capacity of time and informations provided, there are chances that the players are not choosing the most optimal step. With the development of computer technology and an idea from Arthur L. Samuel which was to solve a game using a program, there are various method and algorithms that can help to process and optimize data, one of which is by using machine learning. One of the most used algorithm to predict and classify data is Naive Bayes, this is because the algorithm is quite accurate and efficient. In this study, we will compare Monte Carlo simulation with Naive Bayes. The probability of each model is calculated to create strategies. The Monte Carlo strategy is quite accurate compared to the optimal blackjack strategy by Thorp, but the Naive Bayes prediction strategy is only accurate for when the players decided to stay. The reason why this happens is because the Naive Bayes model is not created based on blackjack’s rules and playbook, but rather based on data.

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