In the field of tourism, serious games are a pedagogical media application that helps players develop travel knowledge and expertise based on game content. A tourism serious game requires a scenario control system to visualize an attractive travel scenario. This paper proposes an Automatic Scenario Control in the serious game to visualize travel recommendation scenarios choice according to the player’s expectations of potential tourism destinations criteria. There are two stages in system development, namely scenario design and scenario selection. In the scenario design stage, we use the Hierarchical Finite State Machine to translate challenge-based stories according to the type of attraction. While at the scenario selection stage, Dynamic Weight Topsis is a method for selecting one of the player’s recommended scenarios. This study uses tourism destinations recommendations as to alternative variables, characteristics of tourism destinations as criteria, and players’ expectations of tourism destinations’ characteristics as weight criteria. In the implementation phase, the tourism serious game uses the content of tourism destinations in Mojokerto Indonesia. The test results show that Automatic Scenario Control generates a preference value for each alternative as a reference for choosing tourism destination scenarios for the player. Three things affect the scenario choice results, including the choice of month of tourist visits, player expectations of tourist destinations, and alternative input from the recommender system.

Smart contracts and Blockchain are necessary for transactions in supply chain management. A smart contract is an agreement in the form of a cryptographic code digitally signed by the actors. This technology holds the data transaction transparently and securely between the actors. The actors may benefit without intermediaries involved in the transaction. Supply chain management will be easily tracked by decentralized data sharing. Supply chain management involves transactions in agricultural sectors such as farmers, Village Cooperatives units, distributors, and consumers. The Cooperative is a party that buys goods from farmers and sells them to consumers. A smart contract is a digital signature that can access the system in transactions. The system records log activities that show the origin of transactions. All actors can see the transaction of agricultural products stored in the blockchain ledger in the Blockchain. This paper discusses blockchain-based smart contracts scenario for supply chain management that is simulated and implemented in the Serious Game. The Game is developed using Unity 3D Development Platform, programming language contract using Solidity, Moralis as Web3 Development Platform and dApp as backend blockchain, Network Environment Polygon Ethereum, and Database that is Redis Enterprise, MongoDB Compass, and Mumbai Testnet.

Background subtraction is the important part of moving object detection. The problem of background subtraction is threshold selection strategy. This paper proposed a Fuzzy C-Means (FCM) algorithm to produce an adaptive threshold for background subtraction in moving object detection. To evaluate the performance, FCM were compared against standard Otsu algorithm as threshold selection strategy. Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR) was used to measure the performance. Based on the experiment, the MSE of FCM is lower than MSE of Otsu and PSNR of FCM is higher than PSNR of Otsu. The result proved that FCM is promising to classify the pixels as foreground or background in moving object detection.

Maintaining player engagement in serious management games is a challenge due to the repetitive nature of traditional predetermined difficulty levels. A dynamic difficulty adjustment (DDA) system is introduced in this study to address this issue by integrating fuzzy logic and Q-learning. Player ennui is frequently the consequence of static difficulty adjustments. In order to dynamically adjust game complexity in accordance with player performance and preferences, our DDA system utilizes a diverse array of performance metrics, adaptive narrative elements, and real-time feedback, as well as fuzzy logic and Q-learning algorithms. According to empirical assessments, players were 28% more effective overall, and play sessions lasted an average of 35% longer. Player satisfaction and involvement were also much improved. Customers played the game longer and were less bored because of the higher degree of difficulty and customization. The integration of fuzzy logic and Q-learning in DDA systems greatly enhances the ability to maintain long-term player engagement in essential management games. This approach offers a long-lasting alternative for creating constantly captivating gaming experiences by effectively reducing the repetitiveness of traditional difficulty adjustments.

Active contours, or snakes, are computer-generated curves that move within images to find object boundaries. They are often used in computer vision and image analysis to detect and locate objects, and to describe their shape. Thus active contour can be used for object segmentation, especially the lesion in medical images. This paper presents the application of active contour models (Snakes) for the segmentation of lesions in dental panoramic image. The aim is to assist the clinical expert in locating potentially cyst or tumor cases for further analysis (e.g. classification of cyst or tumor lesion). In order to apply the snake formulation, color images were converted into gray images. Then, with correct parameters, we can create a snake that is attracted to edges or termination. Initializing contour, choosing parameter value and number of iteration affect the behaviour of the snake in a particular way. Using Receiver Pperating Characteristic (ROC), an average accuracy rate of 99.67 % is obtained. Examples of Snake segmentation results of lesions are presented.

The exoticism of Madura batik has become one of the tourist charm of the Indonesian Madura island. Madura batik created by skilled hands with a high level of artistic imagination to produce diverse and unique batik. Our virtual dressing room use augmented reality technology to create solution of an efficient shopping experience by superimposing the 3D model of a Madura batik cloth within the live Kinect sensor's. The superimposed 3D model of Madura batik will then transformed using 3D rigid transformation and bond to the movements of customer so it appears as if the customer is wearing the virtual dress in the live video view. We built the system using SimpleOpenNi library, and Microsoft Kinect SDK. User Experience (UX) measurement on the adaptation key performance indicators which include Attention, Importance, and Arousal showed 96% of respondents said that they were satisfied while the Quality key performance indicators which include Impression, Valence, and Enjoy showed 97% respondents were satisfied.