Judul: Slow Release Urea Nitrate with Acetaldehyde and Formaldehyde Coating Techniques against Fermentability and In Vitro Digestibility
Abstrak: Penelitian ini bertujuan mengevaluasi pengaruh pemberian coating asetaldehid dan formladehid terhadap fermentabilitas, kecernaan, serta produksi gas dalam rumen secara in vitro. Penelitian ini menggunakan rancangan acak lengkap (RAL) untuk menguji parameter pH, kecernaan bahan kering (KcBK), kecernaan bahan organik (KcBO), konsentrasi amonia, produksi gas, gas metan dan volatile fatty acid (VFA) total serta uji lanjut Tukey HSD. Data yang diperoleh dianalisis dengan menggunakan software SPSS versi 25. Hasil penelitian tersebut menunjukkan bahwa pemberian coating urea nitrat berlapis asetaldehid dan formladehid tidak berpengaruh nyata terhadap pH, KCBK, KCBO, VFA, gas metan dan konsentrasi amonia di dalam rumen. Akan tetapi berpengaruh nyata (P <0,05) dalam menurunkanproduksi gas. Dapat disimpulkan bahwa Penggunaan slow release urea nitrat (SRUN) dengan bahan coating asetaldehid lebih efektif memperlambat laju degradasi amonia dari pada bahan coating formaldehid, namun bahan coating asetaldehid dan formaldehid tidak berdampak terhadap fermentasi rumen, kecernaan, dan produksi metana., This study aimed evaluate the effect of coating acetaldehyde and formaldehyde on fermentability, digestibility, and gas production in the rumen in vitro. This study used a completely randomized design (CRD) to test the parameters of pH, dry matter digestibility (DMD), organic matter digestibility (OMD), ammonia concentration, gas production, methane gas and volatile fatty acid (VFA) ) and differences among mean values were examined using Tukey HSD test. The data obtained were analyzed using SPSS software version 25. The results showed that the coating of urea nitrate coated with acetaldehyde and formaldehyde had no significant effect on pH, DMD, OMD, VFA, methane gas and ammonia concentration in the rumen. However, it had a significant effect (P <0.05) in reducing gas production. The use of slow release urea nitrate (SRUN) with acetaldehyde coating materials is more effective in slowing the rate of ammonia degradation than formaldehyde coating materials, but acetaldehyde and formaldehyde coating materials have no impact on rumen fermentation, digestibility, and methane production.
Keyword: ammonia, acetaldehyde, formaldehyde, urea nitrate coatings

Judul: Utilization Tannin Chesnut (Castenia sp.) as a Protective Agent in Slow Release Nitrogen
Abstrak: Penggunaan urea sebagai penyumbang suplemen pakan utama karena memiliki harga yang murah, mudah dalam pengaplikasian, dan bermanfaat sebagai sumber nitrogen untuk sintesis protein mikroba. Urea memiliki kelemahan salah satunya dapat terhidrolisis cepat menjadi amonia. Solusi dari permasalahan tersebut maka dilakukan mekanisme yang dikenal dengan nitrogen lepas lambat menggunakan tanin jenis terhidrolisis. Penelitian ini bertujuan untuk mengevaluasi rumen in vitro terhadap perlindungan urea dengan menggunakan tanin komersil chestnut dalam berbagai taraf antara lain 0% (P0), 1% (P1), 2% (P2), 3% (P3) ke dalam pakan kontrol. Data dianalisis menggunakan analysis of variance dan perbedaan nyata antar perlakuan dilakukan uji tukey’s hsd test. Hasil penelitian menunjukkan tidak ada perbedaan statistik pada pH rumen, kecernaan bahan kering (KcBK), kecernaan bahan organik (KcBO), dan sintesis protein mikroba (SPM). slow release nitrogen (SRN) berbeda nyata (P<0,05) pada volatile fatty acid (VFA) total. Efek perlindungan berpengaruh negatif terhadap VFA total seiring dengan peningkatan taraf SRN. SRN berbeda sangat nyata (P<0,01) pada produksi amonia. Efek perlindungan berpengaruh negatif terhadap produksi amonia seiring dengan peningkatan taraf SRN. Kata kunci: nitrogen lepas lambat, tanin terhidrolisis, in vitro ABSTRACT FEGGIE. Utilization Tannin Chesnut (Castenia sp.) as a Protective Agent in Slow Release Nitrogen. Supervised by ANURAGA JAYANEGARA and KOMANG GEDE WIRYAWAN. Urea has become indispensable for supplying the necessary feed supplement because of cheap, easy to use, and had a benefit as nitrogen sources for microbial protein synthesis. Urea have a weakness to readly hydrolyzable into amonia. For the solution with use the mechanism that we called slow release nitrogen with hydrolyzable tannin. This experiment was conducted to evaluate in vitro rumen on different levels of tannin chestnut such as 0% (T0), 1% (T1), 2%(T2), 3%(T3) into a control diet. Data were analysed using analysis of variance and any significant different further tested using tukey’s honest significant difference Test. Results this experiment showed addition of different concentration of tannin chestnut as urea protector did not affect with any parameters in pH rumen, dry matter digestibility, organic matter digestibility, and microbial protein synthesis. However, the addition of different concentration of tannin chestnut have negative effects on volatile fatty acid (VFA) total production (P<0,05) and amonia production (P<0,01). Keywords: hydrolyzable tannin, in vitro, slow relase nitrogen
Keyword: hydrolyzable tannin, in vitro, slow release nitrogen

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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