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Bulletin of Artificial Intelligence
Published by CV. Graha Mitra Edukasi
ISSN : -     EISSN : 29623944     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
The field of study of the Bulletin of Artificial Intelligence journal, in the field of Artificial Intelligence, includes: 1) Decision Support Systems, 2) Data Mining, 3) Expert Systems, 4) Big Data, 5) Text Mining, and 6) Natural Language Processing. But does not rule out the possibility of publishing manuscripts in the field of Computer Science.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 2 Documents
 1 
Search results for , issue "vol 3 no 2 (2024): october 2024" : 2 Documents clear
Implementasi Algoritma Sattolo Shuffle Untuk Optimasi Pengacakan Pada Game Solitaire Nasution, Surya Darma; Ginting, Guidio Leonarde
Bulletin of Artificial Intelligence Vol 3 No 2 (2024): October 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i2.200

Abstract

Solitaire is one of the most popular digital card games across various platforms. A critical aspect in the development of solitaire games is the card shuffling mechanism that determines the quality of gameplay experience. Suboptimal shuffling can produce predictable patterns, thereby reducing the challenge and appeal of the game. This study aims to implement the Sattolo Shuffle algorithm as a card shuffling method in solitaire games while evaluating its effectiveness in producing optimal cyclic permutations. The Sattolo Shuffle algorithm is a modification of the Fisher-Yates Shuffle algorithm specifically designed to generate cyclic permutations, where each element is guaranteed to move from its original position. Test results demonstrate that the Sattolo Shuffle algorithm can produce truly random card distributions without repeating patterns across 52 solitaire cards, consistently maintaining game difficulty levels, and providing a more dynamic playing experience compared to conventional shuffling methods. This research contributes to the development of digital card games, particularly in optimizing shuffling mechanisms to enhance gameplay quality
Sistem Pendukung Keputusan Pemilihan Mahasiswa Berprestasi Menggunakan Metode TOPSIS Hutagalung, Dendy Frans Gunawan; Mesran, Mesran
Bulletin of Artificial Intelligence Vol 3 No 2 (2024): October 2024
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v3i2.215

Abstract

Public and private universities are institutions where students acquire knowledge according to their interests and talents. To improve student quality, universities implement programs for selecting outstanding students. However, in many public and private universities, the selection of outstanding students is often based solely on the Grade Point Average (GPA). In fact, several other assessment criteria should also be considered, such as the number of scientific papers, TOEFL score, GPA, ethics, and parents’ monthly income. Therefore, a decision support system is required to assist in the selection process of outstanding students. The method applied in this study is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This method is chosen because it can effectively solve decision-making problems by using priority values or weights assigned to each criterion. The results of this study indicate that Alternative A3, namely “Frans,” is the best alternative with a preference value (Vi) of 1

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