Judul: Studi Pengaruh Intervensi Tempe Untuk Mempercepat Penyembuhan Diare Pada Anak Balita
Abstrak: Diarrhea is a major health problem in many developing countries resulting in the deaths of about 3 million people every year. Tempe is one of diet that could be use in treatment of diarrhea. The objective of this study was to investigate the effect of tempe intervention in the treatment of diarrhea in children under five years of age. The design of this study was experimental study. The number of study participant was 30 children with diarrhea symptoms. Study participants were divided into three treatments group: a) 25 gram, receiving tempe 25 gram for two days; b) 50 gram, receiving tempe 50 gram for two days; c) control, receiving no tempe during five days study period. During the study period, defecation and food habit of the study participants were observed. The result of the study showed that there was no correlation between characteristic of family, eating habit, sanitation and higiene with diarrhea symptoms (P>0,05). However, there was correlation between nutritional status of children with diarrhea symptoms (P<0,05). The duncan test results showed that the average frequency of defecation during five days of study period in children who consumed 50 grams tempe significantly lower (α = 0.05) than the control group. This implies that consumption of tempe have positive effect on the treatment of diarrhea.
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Judul: Penggunaan makanan bayi formula tempe dalam diit bayi dan anak balita sebagai suatu upaya penanggulangan masalah diare
Abstrak: Angka kematian bayi dan balita yang masih tinggi di Indonesia, terutama disebabkan karena diare. Kematian akibat diare selain karena dehidrasi, juga karena dayatahan tubuh penderita menurun yang disebabkan kehilangan zat gizi selama episode diare, mengakibatkan penderita mudah terkena penyakit lain dan keadaan gizi kurang atau buruk.
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Judul: Klasifikasi genre musik menggunakan Learning Vector Quantization (LVQ)
Abstrak: Radio stations and music television have a milion of music tapes. A lot of musical genres create a problem when people wants to determine the right genre of a new kind of music. To classify the musical genre is not an easy task, because the musical genre is really difficult to standardization. Automatic musical genre classification can assist the human role in that process and help people to searching for the song acording to the genre that people want. This research using Mel Frequency Coefficient Cepstrum (MFCC) to obtain feature extraction. Learning Vector Quantization (LVQ), one kind of artificial neural network used for classification method. The number of genres that are used were four kind of musical genre, that is rock, classic, keroncong, and jazz with four different duration that is 5 second, 10 second, 20 second and 25 second. This research using k- fold cross validation to distribute dataset for training and testing set with the number of folds as much as 2 until 10 fold. This research succesfully implemented MFCC feature exraction and classification using LVQ. Based on this research, the accuracy of the classification using Learning Vector Quantization reaches 93,75% for the four type musical genre. The highest accuracy value was obtain from the experiments with a duration of 10 second and the number of fold 4. Training time for each duration is 30 minute for 5 second music duration, 45 minute for 10 second music duration 120 minute for 20 second music duration and 150 minute for 25 second music duration.
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