Judul: Penerapan mel-frequency cepstrum coefficients (mfcc) sebagai ekstraksi ciri pada transkripsi suara ke teks dengan self organizing maps (som)
Abstrak: Transkripsi suara ke teks adalah suatu teknik yang memungkinkan sebuah komputer untuk menerima input berupa kata yang diucapkan dan ditranskripsikan ke dalam sebuah teks. Tujuan penelitian ini adalah mengembangkan suatu sistem transkripsi suara ke teks dengan ekstraksi ciri mfcc dan pemodelan jaringan syaraf tiruan self organizing maps (som). Data yang digunakan adalah data suara yang telah direkam dari satu pembicara yang mengucapkan 15 kata untuk data latih dan 5 kata untuk data uji. Masing-masing kata diulang hingga mencapai 240 data latih dan 50 data uji. Kemudian ciri data suara diekstraksi dengan sampling rate 11000 hz, time frame 23.27 ms, overlap 0.39 ms, dan koefisien cepstral 13 untuk mendapatkan karakteristik dari sinyal suara dalam setiap frame. Percobaan dilakukan dengan mengenali tiap suku kata yang ada pada data uji. Hasil menunjukkan bahwa akurasi tertinggi yang diperoleh sebesar 95% pada kombinasi parameter epoch 10, 30, 50, 70, 90 dan 110, learning rate sebesar 0.5, penurunan learning rate 0.999, dan radius 0
Keyword: ekstraksi fitur, mel-frequency cepstrum coefficients (mfcc), self organizing map, pembicara tunggal, transkripsi

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: Duodenal Histopathology of Pediatric Rat (Rattus norvergicus)&#160;Fed with Orange Juice (Citrus sinensis)
Abstrak: This research investigates the impact of orange juice consumption on the histological structure of the duodenum, a critical site for nutrient absorption and digestion. Focusing on pediatric animals, orange juice (with a pH of 3) was administered to post-weaning rats aged 4 weeks to 6 weeks at dosages ranging from 0g/kg BW to 20g/kg BW over two weeks. Duodenal histopathology was assessed, focusing on parameters such as the quantity of crypts of Lieberkuhn, as well as the length, height, width, and depth of villi (measured in µm). Anatomical pathology examination included measurements of the length and width of the duodenum (also in µm), as well as the color mean (OD). The research findings indicate no significant changes in histopathology or anatomy pathology of the duodenum. This suggests that young individuals can adapt to acidic challenges without compromising gastrointestinal health. These findings offer reassurance regarding the short-term consumption of acidic orange juice (with a pH of 3) with minimal risks to intestinal integrity, both during growth and development.
Keyword: acidic changes