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Proceedings of KNASTIK
Published by Universitas Kristen Duta Wacana
ISSN : -     EISSN : -     DOI : -
Core Subject :
Arjuna Subject : -
Articles 144 Documents
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PEMODELAN PROBABILISTIK NEURAL NETWORK UNTUK KONVERSI SUARA GITAR KE CORD Rizki, Arviani; Buono, Agus
Proceedings of KNASTIK 2013
Publisher : Duta Wacana Christian University

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Abstract

Almost allmusic genreuse guitaras its instrument.Toproducea harmonicguitarvoice needs guitar chords mastery. However, only few peopleareable todistinguish guitar chords. This paper is addressed to develop a computational model to convert guitar voice into appropriate cord. In this research, we use Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction because thistechniqueis oftenusedfor voice processing and good enough in presenting thecharacteristics ofasignal voice. Probabilistic Neural Network (PNN) is implemented to classify the feature into one out of 24 classes of cord. We record 345 for each cord (totally we have 8640 recording data with WAV format). Experimenst are conducted for some number of cepstral coefficients (13, 26, 39 and 52), with 100 millisecond as time frame and 40% overlapping between successive frame. According to the experiment, the maximum accuracy is 94.31% for 52 number of cepstral coefficients.
PEMODELAN JARINGAN SYARAF TIRUAN RESILIENT BACKPROPAGATION UNTUK KONVERSI SUARA GITAR KE CORD Nurhayati, Yosi; Buono, Agus
Proceedings of KNASTIK 2013
Publisher : Duta Wacana Christian University

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Abstract

The guitar is a musical instrument that has a chord as a reference tone. It is a fact that is not all human auditory system can distinguish between high and low tones of a musical instrument in good accurate. Then, in this research we develop a voice guitar to cord conversion using resilient backproagation neural network (RBNN) as to classifier and Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction. We record 345 for each cord (totally we have 8640 recording data with WAV format). Experiments are conducted for some number of cepstral coefficients (13, 26, and 39), with 100 millisecond as time frame and 40% overlapping between successive frame. Total number of hidden neurons in RBNN model in this experiments are 10, 25, 50 and 100. According to the experiment, the maximum accuracy is 96.88% for 52 number of cepstral coefficients and 100 neurons hidden.
Penerapan Metode Simple Additive Weighting Pada Penentuan Tingkat Kesejahteraan Penduduk Provinsi Nusa Tenggara Timur Kaho, Monica Louisa Ratu; Tanaamah, Andeka Rocky; Wowor, Alz Danny
Proceedings of KNASTIK 2013
Publisher : Duta Wacana Christian University

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Abstract

The importance of a system not only helping the work done quickly and easy but also could result accurate information. Recently many government's program especially related with society walfare those are not touch the right target because the inaccurate information about society welfare. Answering this problem, we need a system that resulting the accurate information about people welfare. To determine the level of people walfare use many criteria and alternative, to easing the determination of welfare level we need to applying Simple Additive Weighting method on the system because Simple Additive Weighting is one of completion method that involve many criteria and alternative. Through the information that result by the system that is level of people welfare in each regency of East Nusa Tenggara, hopefully could help the authority to determine which region to be priority for the implementation of the welfare developing program.
IMPLEMENTASI AUGMENTED REALITY DI MUSEUM: STUDI AWAL PERANCANGAN APLIKASI EDUKASI UNTUK PENGUNJUNG MUSEUM Yudiantika, Aditya Rizki; Pasinggi, Eko Suripto; Sari, Irma Permata; Hantono, Bimo Sunarfri
Proceedings of KNASTIK 2013
Publisher : Duta Wacana Christian University

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Abstract

Augmented Reality (AR) dikenal sebagai teknologi interaktif yang mampu memproyeksikan objek maya ke dalam objek nyata secara real time. Perkembangan teknologi AR dewasa ini telah memberikan banyak kontribusi ke dalam berbagai bidang. Salah satu implementasi AR di bidang edukasi dan hiburan yaitu pemanfaatan AR dalam museum. Aplikasi AR yang diujicobakan dalam penelitian ini terdiri dari dua jenis, yaitu AR Desktop dan AR Mobile. Pengujian dilakukan dengan melakukan studi aplikasi dan studi pengguna. Pengunjung diminta untuk menggunakan beberapa aplikasi AR yang disediakan. Kemudian reaksi pengunjung diamati untuk menentukan kebutuhan pengguna. Beberapa pertimbangan dihasilkan dari penelitian ini. Metode pelacakan objek dengan jumlah marker yang terlalu banyak dinilai mengganggu tampilan ruang pamer museum. Aplikasi AR Desktop lebih tepat digunakan untuk menampilkan konten informasi secara detail. Sedangkan aplikasi AR Mobile mempunyai keunggulan karena sifatnya yang mudah berpindah. Penelitian ini juga membahas studi lain mengenai jenis konten, pengaruh pencahayaan, dan kesan pengunjung saat menggunakan aplikasi AR.

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