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@article{JMASIF8456, author = {Sukmawati Endah and Dinar KN}, title = {KLASIFIKASI UCAPAN KATA DENGAN SUPPORT VECTOR MACHINE}, journal = {Jurnal Masyarakat Informatika}, volume = {3}, number = {6}, year = {2012}, keywords = {Support Vector Machine, klasifikasi ucapan kata}, abstract = {Menurut Undang-Undang No 32 Tahun 2002, Peraturan Komisi Penyiaran Indonesia No 02/P/KPI/12/2009 tentang Pedoman Perilaku Penyiaran dan Peraturan Komisi Penyiaran Indonesia No 03/P/KPI/12/2009 tentang Standar Program Siaran, diantaranya disebutkan bahwa program siaran tidak boleh memaki dengan kata-kata kasar, tidak boleh melecehkan, menghina atau merendahkan kelompok masyarakat minoritas dan marginal. Namun untuk mensensor kata-kata tersebut secara otomatis belum ada. Sehingga perlu adanya suatu perangkat lunak cerdas yang dapat menyensor kata-kata tersebut secara otomatis. Untuk dapat menyensor, perangkat lunak harus mampu mengenali kata-kata yang dimaksud. Penelitian ini mengusulkan pengklasifikasian ucapan kata dalam dua kelas, yaitu kelas kata-kata yang berisi makian kasar dan kelas kata yang bukan termasuk kata makian dengan menggunakan metode Support Vector Machine (SVM). Data ucapan kata yang diambil merupakan data suara untuk kelompok umur 19 – 21 tahun yang terdiri dari 19 pria dan 8 wanita. Masing-masing orang mengucapkan 25 kata makian kasar dan 25 kata yang bukan termasuk kata makian. Berdasarkan hasil eksperimen dengan melibatkan 25 data training dan 25 data testing, untuk suara pria menghasilkan tingkat keakuratan sebesar 78,4% dan untuk suara wanita menghasilkan tingkat keakuratan sebesar 80%.}, issn = {2777-0648}, pages = {7--14} doi = {10.14710/jmasif.3.6.8456}, url = {https://ejournal.undip.ac.id/index.php/jmasif/article/view/8456} }
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