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: Penerapan Model Codebook untuk Transkripsi Suara ke Teks dengan Ekstraksi Ciri Mel-Frequency Cepstrum Coefficients (MFCC)
Abstrak: The advancement of information technology has triggered various demands in utilizing computer. One of them is to make computers able to communicate naturally with humans. This study uses MFCC as a feature extraction method and codebook as a pattern recognition method for voice-to-text transcription. The clustering technique used in this study is k-means. Data obtained from MFCC are clustered using the k-means method, and the model for classification is constructed using the codebook method. The utilized MFCC parameters are sampling frequency 11 000 Hz, time frame 23.27 ms, overlapping 39%. 300 voice data in WAV files with 5 seconds of duration each, are used as the training data and test data to determine the number of cepstral coefficients and the number of cluster that can produce the highest accurancy. The experiment is conducted by recognizing each syllable in 60 the test data with 240 training data. Simulation result shows that the maximum accurancy obtained is 98.3% at 26 cepstral coefficients and 12 clusters.
Keyword: voice transcription, MFCC, k-means, codebook

Judul: Pola Pernikahan Masyarakat Batak Karo di Perantauan
Abstrak: Pernikahan adalah budaya yang tidak akan pernah berhenti, pernikahan akan terjadi secara berkelanjutan Dasarnya, karena pernikahan merupakan kebutuhan biologis manusia. Indonesia adalah negara yang kaya akan budaya dan etnis. Setiap suku di Indonesia mempunyai tata cara/adat istiadat dalam pelaksanaan pernikahan itu sendiri. Begitupun dengan suku Batak karo yang mempunyai sendiri tata cara pelaksanaan pernikahan. Seiring dengan perkembangan zaman Karo Banyak masyarakat yang merantau ke berbagai daerah di Indonesia, salah satunya Bogor berjalan-jalan. Masyarakat Karo yang merantau ke wilayah Bogor pada umumnya akan berusaha melakukan adaptasi ke negara tempat tinggal baru. Keadaan ini juga terjadi pada perkawinan Karo dalam pola adaptasi di Bogor. Namun adaptasi pernikahan masyarakat Karo di Bogor berupaya menjaga nilai-nilai budaya Karo dan sakralisme perkawinan. Mereka do Karo Dimodifikasi pada pola perkawinan, dengan tetap menjaga nilai budaya pernikahan.
Keyword: Weddings Karo, Adaptation marriage patterns, Attitudes