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All Journal International Journal of Electrical and Computer Engineering Majalah Forum Teknik UGM INOTEKS : Jurnal Inovasi Ilmu Pengetahuan, Teknologi, dan Seni Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Forum Nuklir Proceedings of KNASTIK Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Ilmiah Kursor Jurnal Teknologi Prosiding SNATIF Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) Proceeding of the Electrical Engineering Computer Science and Informatics Conference SENATIK STT Adisutjipto Yogyakarta Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Nasional Teknik Elektro dan Teknologi Informasi Pancaran Pendidikan Jurnal INFOTEL
Risanuri Hidayat
Departemen Teknik Elektro Dan Teknologi Informasi, Fakultas Teknik Universitas Gadjah Mada
Aerospace Engineering Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Physics

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Journal : Jurnal Ilmiah Kursor

 1 
SPEECH RECOGNITION OF KV-PATTERNED INDONESIAN SYLLABLE USING MFCC, WAVELET AND HMM Syahroni Hidayat; Risanuri Hidayat; Teguh Bharata Adji
Jurnal Ilmiah Kursor Vol 8 No 2 (2015)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i2.63

Abstract

The Indonesian language is an agglutinative language which has complex suffixes and affixes attached on its root. For this reason there is a high possibility to recognize Indonesian speech based on its syllables. The syllable-based Indonesian speech recognition could reduce the database and recognize new Indonesian vocabularies which evolve as the result of language development. MFCC and WPT daubechies 3rd (DB3) and 7th (DB7) order methods are used in feature extraction process and HMM with Euclidean distance probability is applied for classification. The results shows that the best recognition rateis 75% and 70.8% for MFCC and WPT method respectively, which come from the testing using training data test. Meanwhile, for testing using external data test WPT method excel the MFCC method, where the best recognition rate is 53.1% for WPT and 47% for MFCC. For MFCC the accuracy increased asthe data length and the frame length increased. In WPT, the increase in accuracy is influenced by the length of data, type of the wavelet and decomposition level. It is also found that as the variation of state increased the recognition for both methods decreased.
IMPLEMENTATION OF FACE RECOGNITION USING GEOMETRIC FEATURES EXTRACTION Risanuri Hidayat; Muhammad Oka Bagus Wibowo; Brama Yoga Satria; Anggun Winursito
Jurnal Ilmiah Kursor Vol 11 No 2 (2021)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v11i2.284

Abstract

The face is among the biometric objects used to recognize one’s identity. There are various face recognition system methods that can be applied, one of which is geometric features-based face recognition. Geometric features are unique features extraction of one’s facial components. These features are obtained by calculating the comparison values of the distance measurement between facial components served as a reference like eyes, nose, and mouth. This research implemented a face recognition system using the geometric features method on a significantly low-spec computer system. This implementation was carried out by building a system, installing it on a computer system, and then testing it using laptops or computer devices and the camera web. The face recognition system would process the facial input images, extract their geometric features, and match the results with the data stored in the database. The research results were a low-spec computer system that could recognize its users by providing real-time feedback in the form of users’ names with an accuracy of 98%.
Co-Authors Achmad Noerkhaerin Putra Achmad Rizal Adha Imam Cahyadi Adhi Susanto Agus Bejo, Agus Ahmad Fauzi Haqqoni Ahmad Nugroho Jati Akhmad Anggoro Akhmad Anggoro Akhyar Akhyar Akhyar Akhyar Albertus Joko Santoso Anggoro, Akhmad Anggun Fitrian Isnawati Anggun Winursito Bimo Sunarfri Hantono Brama Yoga Satria Budi Setiyanto Budi Setiyanto Budi Setiyanto Domy Kristomo Dwiyanto Dwiyanto Eka Firmansyah Eka Firmansyah Eka Wahyudi Eka Wahyudi Elfrida Ratnawati Fitrah Sugita, Muhammad Gede Bayu Suparta Hanung Adi Nugroho Herdjunanto, Samiadji Hutagalung, Robertus Halomoan I Wayan Mustika Ida Bagus Verry Hendrawan Manuaba Ikhsan Shobari Indah Soesanti Irwan Novianto Isbadi Urifan Iswandi Jazi E Istiyanto Jazi E. Istiyanto Koko Joni Lasmadi Lasmadi Lukito Edi Nugroho Mingsep Rante Sampebua Mohammad Yanuar Hariyawan Muhammad Fitrah Sugita Muhammad Oka Bagus Wibowo Muhammad Sonnie Bestian Nugroho, Anan Oyas Wahyunggoro Rachman, Anung Rachmawati Rachmawati Rachmawati Risky Via Yuliantari Robertus Halomoan Hutagalung Samiadji Herdjunanto Samiadji Herdjunanto Samiadji Herdjunanto Samuel Kristiyana Sani Tanaka Isnawanto Selo Sulistyo, Selo Siti Helmyati Sri Suning Kusumawardani Sujoko Sumaryono Sunarno Sunarno Sunarno Sunarno Sunarno Sunarno Sunarno Sunu Wibirama Syahroni Hidayat Teguh Bharata Adji Verry Hendrawan Manuaba, Ida Bagus Wening Mustikarini Willy Anugrah Cahyadi