Rika Jane Ardiadna, Abas Setiawan

Adaptive Difficulty in Earthquake Mitigation Game Using Fuzzy Mamdani

Introduction

Adaptive difficulty in earthquake mitigation game using fuzzy mamdani. Learn earthquake mitigation effectively with an adaptive difficulty game powered by Fuzzy Mamdani logic. This educational tool adjusts challenges based on player ability to prevent boredom.

Abstract

Abstract. Earthquake disasters cause a lot of casualties. Therefore, needs to be education on earthquake disaster mitigation to minimize losses. In addition to counseling and teaching in schools, mitigation education can also be through games. Some education games for earthquake disaster mitigation have circulated quite a lot but have disadvantages, namely the difficulty level that hasn't been adaptive. A game requires an adaptive level of difficulty that can adjust between the ability and playing experience of the player with the level of difficulty so that players do not feel bored or frustrated.Purpose: This study aims to provide earthquake disaster mitigation education and discuss making the level of difficulty in the game adaptive to suit the abilities and experience of the player.Method: From the research carried out by applying the Mamdani Fuzzy Logic, the game's difficulty level for each player becomes more adaptive or different for each player according to the ability and experience of each player in the previous stage measured from 6 input parameters.Result: The level of difficulty that is obtained becomes adaptive. It changes according to conditions or is adjusted based on the player's ability. It is from the playtesting experiment conducted on 20 players. The minimum difficulty level's score is five, and the difficulty level's score is 28.36.Novelty: This paper's purpose is an educational game for earthquake mitigation with the feature of adaptive level based on fuzzy Mamdani.

Review

This paper presents a timely and highly relevant solution to a critical societal need: enhancing earthquake disaster mitigation education. The authors propose an innovative approach by developing an educational game that addresses a common drawback in existing educational games – static difficulty levels. By introducing an adaptive difficulty system powered by Fuzzy Mamdani logic, the study aims to create a more engaging and effective learning experience, preventing player boredom or frustration. This focus on personalized learning, where the game adjusts to the player's ability and experience, holds significant promise for improving the efficacy of educational tools in disaster preparedness. The methodology employed involves the application of Fuzzy Mamdani logic, which is designed to dynamically adjust the game's difficulty. The abstract indicates that this adjustment is based on six input parameters, intended to measure the player's ability and experience accumulated in previous game stages. The stated novelty lies in providing an educational game for earthquake mitigation equipped with this specific adaptive difficulty feature. Initial playtesting experiments with 20 players are reported, yielding a range of difficulty scores from 5 to 28.36, which the authors present as evidence of the system's adaptive nature and its ability to tailor the challenge to individual conditions. While the abstract outlines a promising concept, a more comprehensive understanding would benefit from additional detail. To fully assess the proposed Fuzzy Mamdani system, it would be crucial to explicitly define the "6 input parameters" that inform the difficulty adjustments, as these are central to the system's operation. Furthermore, beyond reporting a range of difficulty scores, the paper would be significantly strengthened by including qualitative or quantitative data from the playtesting related to player engagement, perceived adaptiveness, and direct feedback on whether boredom or frustration were effectively mitigated. A comparative analysis, perhaps against a game with a non-adaptive difficulty or alternative adaptive mechanisms, would also provide valuable context and underscore the unique advantages of the Fuzzy Mamdani approach in this educational context.

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