Wall Pattern Detection with Prim’s Algorithm to Create Perfect Random Maze

Istiono, Wirawan (2023) Wall Pattern Detection with Prim’s Algorithm to Create Perfect Random Maze. Journal of Theoretical and Applied Information Technology, 101 (09). pp. 3431-3438. ISSN 1817-3195 (Unpublished)

Text WALL PATTERN DETECTION WITH PRIM’S ALGORITHM TO CREATE PERFECT RANDOM MAZE.pdf Download (1MB)

Abstract

Replayability is one of the factors that determines how a video game played again by players, with one of the example is by offering new and unique content into a game. One of the methods that can be used is by implementing a map generation into the game level via Procedural Content Generation or PCG. With Prim’s Algorithm as the base of the PCG, this research will design and develop a game with mazes as its map level. Focusing on their maze generation, this research will also on the result and will try to detect and display the data of mazes generated, while also trying to determine video game satisfaction from players that will be playing the game developed via Game User Experience Satisfaction Scale or GUESS. A Detect Wall Pattern method is developed to detect the pattern of each mazes’ grids, where the data will be documented and then processed to determine the result of 250 maze generations of mazes with size 2x2, 3x3 and 4x4. Based on the research, MazeGame has succeeded on being developed with PCG feature based on Prim’s Algorithm. Detect Wall Pattern method has also been developed successfully, where this method successfully detecting 4 unique patterns for 2x2 size mazes, 79 patterns for 3x3 size mazes, and 243 patterns for 4x4 size mazes from 250 maze generation on each size.

Item Type:	Article
Creators:	Istiono, Wirawan
Contributors:
Keywords:	Replayability, Procedural Content Generator, Prim’s Algorithm, MazeGame, GUESS, Detect Wall Pattern
Subjects:	000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 004 Computer Science, Data Processing, Hardware > 004.6 Internet, Cloud Computing, Website, LAN, Email 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming
Divisions:	Faculty of Engineering & Informatics > Informatics
Date Deposited:	09 Sep 2025 01:25
URI:	https://kc.umn.ac.id/id/eprint/40041

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