In the era of information technology, a lot of data can be taken from human activities based on computer systems. But the system is not only found on computers, but in all areas of human life, be it in terms of health, security, even in games where the data set from these activities becomes a database that can be used to find a new knowledge. This study aims to predict the accuracy of poker games using the Weight Improved Particle Swarm Optimization (WIPSO) algorithm for attribute selection which then uses the C5.0 algorithm to predict accuracy. Before being processed, the dataset will be changed from 11 attributes to 6 attributes. The results of this study indicate that the accuracy of the poker card will increase, when using the C5.0 algorithm the accuracy obtained is 49.952% while the accuracy obtained by the C5.0 + WIPSO algorithm is 51.2%.
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