The 1st International Conference on Computer Science and Engineering Technology Universitas Muria Kudus

Research Article

Determination Model of Tectonic Seismicity Level In Earthquake Early Warning System By Implementing ANFIS (Adaptive Neuro Fuzzy Inference Systems)

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  • @INPROCEEDINGS{10.4108/eai.24-10-2018.2280617,
        author={Setyawan D.Y and Yuliawati D and Warsito Warsito and Warsono Warsono},
        title={Determination Model of Tectonic Seismicity Level In Earthquake Early Warning System By Implementing ANFIS (Adaptive Neuro Fuzzy Inference Systems)},
        proceedings={The 1st International Conference on Computer Science and Engineering Technology Universitas Muria Kudus},
        publisher={EAI},
        proceedings_a={ICCSET},
        year={2018},
        month={11},
        keywords={anfis earthquake},
        doi={10.4108/eai.24-10-2018.2280617}
    }
    
  • Setyawan D.Y
    Yuliawati D
    Warsito Warsito
    Warsono Warsono
    Year: 2018
    Determination Model of Tectonic Seismicity Level In Earthquake Early Warning System By Implementing ANFIS (Adaptive Neuro Fuzzy Inference Systems)
    ICCSET
    EAI
    DOI: 10.4108/eai.24-10-2018.2280617
Setyawan D.Y1,*, Yuliawati D1, Warsito Warsito2, Warsono Warsono2
  • 1: IIB Darmajaya Lampung
  • 2: Lampung University
*Contact email: dodi@darmajaya.ac.id

Abstract

Determination Model of tectonic seismicity level using ANFIS method in the real time earthquake early warning system will be described in this research. the system is based on the data from monitoring tectonic activities using flux magnet sensor, ground temperature sensor and Radio Frequency. The system learning uses recursive square estimator algorithm (RSQ) and backpropagation gradient descent. It results in an error value of 1.1527 for epoch 100 in the training process. Whereas, the test process results in an error value of 1.1527 and in outline that the result of determination with ANFIS is close to the actual value of the seismicity level.