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All Journal Journal of Computer System and Informatics (JoSYC) Bulletin of Artificial Intelligence
Guidio Leonarde Ginting
Sekolah Tinggi Ilmu Manajemen Sukma Medan, Medan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering

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Penerapan Algoritma Sattolo Shuffle dalam Sistem Pengacakan Denah Tempat Duduk Peserta Ujian untuk Mencegah Kecurangan Akademik Surya Darma Nasution; Guidio Leonarde Ginting
Bulletin of Artificial Intelligence Vol 4 No 2 (2025): October 2025
Publisher : Graha Mitra Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62866/buai.v4i2.236

Abstract

Academic cheating during examinations remains a serious problem in educational institutions. One contributing factor is the use of fixed and predictable seating arrangements, which allow exam participants to plan cheating strategies with nearby peers. This study aims to implement the Sattolo Shuffle algorithm in a seating arrangement randomization system for exam participants as a measure to prevent academic dishonesty. The Sattolo Shuffle algorithm was chosen because of its ability to generate cyclic permutations that guarantee every element moves from its original position, ensuring no exam participant occupies the same seat as in a previous exam. The study was conducted using an experimental approach involving 30 exam participants randomized using the Sattolo Shuffle algorithm. The shuffling process requires 29 iterations (n-1 iterations for n=30 elements), and the verification results show that no participant remains in their original position (0 fixed points), proving the algorithm successfully produces a perfect cyclic permutation. All 30 participants form a single cycle, confirming the derangement property of the Sattolo Shuffle algorithm
Sentiment Analysis of Tokopedia Customer Reviews using IndoBERT and SMOTE for Class Imbalance Handling Imam Saputra; Mesran Mesran; Guidio Leonarde Ginting
Journal of Computer System and Informatics (JoSYC) Vol 7 No 1 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v7i1.8748

Abstract

Sentiment analysis in the Indonesian e-commerce sector faces significant challenges due to the informal nature of language and severe class imbalance, where neutral reviews are often underrepresented. This research proposes a hybrid framework combining the deep semantic capabilities of IndoBERT with the Synthetic Minority Over-sampling Technique (SMOTE) to improve classification fairness. Using a dataset of Tokopedia customer reviews, this study compares a baseline model against a balanced model using SMOTE on 768-dimensional IndoBERT features. The experimental results reveal that while the baseline model achieved a high overall accuracy of 83%, it suffered from an "accuracy paradox," exhibiting a dismal recall of only 0.07 for the neutral class. Upon implementing SMOTE, the neutral class recall surged to 0.29, marking a significant 314% improvement in minority class detection. Although overall accuracy slightly decreased to 81%, the Macro Average F1-Score increased from 0.61 to 0.65, proving that the model is more robust and objectively reliable across all sentiment polarities. This study demonstrates that sacrificing marginal accuracy for improved minority sensitivity is vital for providing accurate business intelligence in the digital marketplace. These findings provide a robust roadmap for developing more equitable automated sentiment analysis systems in Indonesia.
Implementasi Algoritma Sattolo Shuffle Untuk Optimasi Pengacakan Pada Game Solitaire Surya Darma Nasution; Guidio Leonarde Ginting
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
Co-Authors Imam Saputra Mesran Mesran Surya Darma Nasution