@article{MAKHILLJEAS2019142318719,
    title = {Dance Recognition System of Sigeh Penguten Traditional Dance based on
Hidden Markov Model},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {23},
    pages = {8668-8675},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.8668.8675},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.8668.8675},
    author = {Aciek,Maria,Khairurijal,Marzuki,Agus,Egi Muhamad,Ary Setijadi and},
    keywords = {Traditional dance,Hidden Markov Model,3D character,Sigeh Penguten,kinect,Lampung},
    abstract = {Culture is one of the characteristics created by a group of people inherited from generation to
generation. Among various kinds of cultural diversity in Indonesia, cultural arts are one of the cultural riches
admired by other countries as well as on dance. Indonesian traditional dance, one of them is Sigeh Penguten
dance is a typical dance from Lampung Province to welcome honored guests at certain occasions. Therefore,
it is necessary to maintain its sustainability by modeling the dance using the Hidden Markov Model with the
representation of the skeleton taken using the Kinect V2 camera. In this research, the phrase modeling using
HMM is done on several phrases. The results of the phrase recognition on the dance model were built using
Hidden Markov Model (HMM). The results of the dance recognition of the Sigeh Penguten traditional dance
will be simulated on the 3D character of the Sigeh Penguten dancer. Motion simulation is generated from the
transformation of data in the form of movements from humans to 3D characters.}
    }