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Comparative Analysis of the Performance Testing Results of the Backtracking and Genetics Algorithm in Solving Sudoku Games Indriyono, Bonifacius; Pamungkas, Natalinda; Pratama, Zudha; Mintorini, Ery; Dimentieva, Imelda; Mellati, Pita
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 5 No. 1 (2023): May 2023
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v5i1.6501

Abstract

Games that hone thinking skills and logical accuracy have recently been very popular. One of them is the game Sudoku. Sudoku is a game that hones logic through puzzles arranged in rows and columns. Sudoku is also defined as a puzzle game that aims to arrange several numbers in a grid from one to nine on a grid consisting of 9x9 squares. The concept of this Sudoku game is to enter numbers into the rows and columns provided. The rule of this game is that the numbers arranged on the board cannot be the same in every row, column, and 3x3 square in the grid. In another sense, each number entered must appear once in each row and column. When running Sudoku, several numbers are already instructions for players to fill in the next boxes. The number of clues at the beginning of the game determines the difficulty level players face. The fewer clues, the more difficult the Sudoku is to solve. This study aims to compare how to solve Sudoku using genetic algorithms, backtracking, and the completion time needed. The tests' results show that the genetic and backtracking algorithms can solve Sudoku games quickly. Still, the backtracking algorithm has the advantage of being relatively shorter, and the process is not so complicated that the backtracking algorithm can be an alternative solution to solving Sudoku logic games.
Identifikasi Teknik Data Mining Metode Asosiasi: Systematic Literature Review Lutfina, Erba; Yuanita, Syafira Putri; Dimentieva, Imelda; Pribadi, Ahmad Naufal; Syahidan, Mukhammad Shaunan; Safa’at, Mochammad Alief Fauzan Akbar; Loekito, Joseph
Science Technology and Management Journal Vol. 4 No. 2 (2024): Agustus 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Nasional Karangturi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53416/stmj.v4i2.257

Abstract

Data mining is a process of collecting important information from large data. Data mining has many functions, one of which is the description function. In this case, the description function is that later data mining can find certain patterns hidden in data. This research aims to identify which association methods in data mining are most often used, identify the most dominant dataset models in association methods, identify the most relevant journal years in association methods, identify what fields most often use association methods, and find out the objectives of researchers using association methods such as FP-Growth and Apriori in various related journals. Using a Systematic Literature Review (SLR) approach, to answer the research questions that have been prepared from the analysis with a total of 33 related journals. So as a result, this study shows that the application of the SLR method can provide answers to the research questions that have been prepared.