<![CDATA[This research develop the settlement mechanism in Real Time Grass Settlement by using Clearinghouse through serious game. Banks are represented as nodes that settlement process requests, then settled according to the set of simple rules. This research apply Graph mining approach for predicting activity network which will be formed. The result of this research indicate that amount of node are same, more of activity networks between banks hence is more Graph identified. While degree between 0 to 2, the smaller difference of the bank health level, which will forming network, the greater Graph available for identified. While for degree which more than 2 no Graph available for detected, this condition caused of fixed point behavior. Testing by using l = 0.7, x started with degradation drastically towards stable value come near 0. l = 1.8, x started with degradation drastically value towards stable value, but stability value still not yet come near 0. l = 2.9, x oscillate about fixed point and convergence. While l = 3.9, x start oscillation Kata Kunci: Real Time Grass Settlement, Clearinghouse, settlement, prediksi jaringan kerja, Graph mining, Serious game  ]]>
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