Judul: Implementasi hidden markov model untuk aplikasi pengenalan ucapan sebagai kendali gerak robot mobil
Abstrak: Robot is an electronic or mechanical equipment capable of performing a series of actions automatically. In the world of robotics, control systems is a very important part that serves to control the movement or navigation in a robot. Sound based mobile control system is an alternative voice control that is quite efficient. However, voice recognition process is not easily done by a machine. It needs a machine learning method that can be used to perform the voice feature extraction by studying the characteristics of a previous vote. This study uses Mel-Frequency Cepstral Coefficient (MFCC) to extract speech signal and HMM (Hidden Markov Model) for modeling the speech signal. Result of the experiment from the whole system performance speech recognition is 96,4% for people that have been inputted in the database, and 91,2% for people which have not been inputted in database. The mobile robot system test results showed that the system has worked well and has an average response time to move after the speech recognition process around 0,46 seconds.
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Judul: Penerapan Learning Vector Quantization (LVQ) dan Ekstraksi Ciri Menggunakan Mel-Frequency Cepstrum Coeffecients (MFCC) untuk Transkripsi Suara ke Teks
Abstrak: Speech recognition by a computer is not an easy thing to do. Speech to text transcription is a technique that allows a computer to accept input in the form of spoken words and convert it into text. The purpose of this study is to model the neural network namely Learning Vector Quantization (LVQ) for speech to text transcription and determine the accuracy of speech recognition using MFCC feature extraction. The experiments are conducted by recognizing each syllable of the test data. The results show that the highest accuracy is 98.57% when the epoch value is 90, learning rate is 0.007, and learning rate decrement factor is 0.977. This accuracy is obtained by using the following MFCC parameters: sampling rate 11000 Hz, time frame 23.27 ms, overlap 0.39, and cepstral coefficients 13.
Keyword: voice, transcription, Mel-Frequency Cepstrum Coefficients (MFCC), Learning Vector Quantization (LVQ)

Judul: Leucocytozoonosis Pada Ayam Ras di Sumatera Utara
Abstrak: Di Propinsi Sumatra Utara penyakit leucocytozoonosis pada ayam ras yang disebabkan oleh Leucocytozoon caulleryi dilaporkan oleh Balai Penyidikan Penyakit Hewan wilayah I Medan untuk pertama kali pada bulan Oktober 1982. Penyakit ini mula-mula ditemukan pada ayam broiler berumur 2-3 bulan di Kampung Purwodadi, Kecamatan Medan Sunggal, Kabupaten Deli Serdang. Pada penyidikan terhadap penyakit leucocytozoonosis ini dibeberapa peternakan ayam ras di Kabupaten Deli Serdan Kotamadya Medan ternyata bahwa penyakit ini menimbulkan mortalitas sebesar 20% dan morbiditas 50-100%. Cara mendiagnose yang dipergunakan masih perlu ditingkatkan untuk memperoleh angka mortalitas dan morbiditas yang lebih cermat. Pemakaian gel precipitation test dianjurkan. Penyakit ini diketahui menyerang ayam ras yang dipelihara pada daerah persawahan, daerah yang penuh dengan semak belukar dan keadaan tanah yang lembab dan basah serta banyak air yang tergenang. Ayam yang terserang berumur 2-3 bulan. Diduga penyakit ini ditularkan melalui agas (Culicoides).
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