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Arif, Yunifa Miftachul, Nurhayati, Hani, Karami, Ahmad Fahmi, Nugroho, Fresy 
ORCID: https://orcid.org/0000-0001-9448-316X, Kurniawan, Fachrul ORCID: https://orcid.org/0000-0002-3709-8764, Rasyid, Harits, Aini, Qurrotul, Diah, Norizan Mat and Garcia, Manuel B.
(2023)
An artificial neural network-based finite state machine for adaptive scenario selection in serious game.
International Journal of Intelligent Engineering & Systems, 16 (5).
pp. 488-500.
ISSN 2185-3118
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Abstract
Serious game is one of the pedagogical media capable of transferring knowledge to its players. This game genre requires a support system that adaptively selects the appropriate scenario for players to increase their interest and comfort. Therefore, this study proposed an adaptive scenario selection (ASS) system using a finite state machine based on an artificial neural network (ANN). The game scenario is selected by ASS based on five player preferences, including work, hobbies/interests, origin, group members, and repetition. Furthermore, the multi-layer perceptron (MLP) architecture was used in the scenario selection process for the proposed ANN method. The experimental stage was carried out using the theme of travel in several tourism destinations in Batu City, East Java, Indonesia. The experimental results show that ASS succeeded in generating adaptive game scenario choices for players based on their preference data with an accuracy of 67.25%.
| Item Type: | Journal Article |
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| Keywords: | serious game; adaptive scenario; player preference; neural network; finite state machine. |
| Subjects: | 08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software > 080305 Multimedia Programming |
| Divisions: | Faculty of Technology > Department of Informatics Engineering |
| Depositing User: | Fresy Nugroho |
| Date Deposited: | 20 Sep 2023 16:03 |
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