Judul: Perbandingan Metode Ekstraksi Ciri FFT, PCA, dan FPE dalam Pengenalan Karakter Tulisan Tangan
Abstrak: The main purpose of this research is to create a fully functioned system to translate any handwritten mathematic expression into LaTeX code. This research itself serves as one of the basic part of the system, the handwritten character recognition system. Three feature extraction methods were compared and evaluated. They are Feature Point Extraction, Principle Components Analysis, and Fast Fourier Transform. Classification method used in this research is K-Nearest Neighbors. Accuracy measurement of the three methods shows that the maximum accuracy score by Feature Point Extraction is around 26%, while Principle Component Analysis and Fast Fourier Transform score is approximately 60% and 70%, respectively. FPE, despite its high score on optical character recognition (around 86% accuracy score), did not perform well due to the fact that the FPE method used in this research did not aware of the position of each feature point. PCA and FFT proved to be better for handwritten character recognition, with FFT being the one to have the highest accuracy score.
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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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