Judul: Pengaruh Trass dan Pupuk Fosfor terhadap Produksi Padi serta Perubahan Sifat Kimia Tanah Sawah
Abstrak: Indonesia adalah salah satu negara yang mengkonsumsi beras tertinggi di dunia. Lahan sawah sebagai sumber utama penghasil beras saat ini semakin berkurang akibat konversi lahan pertanian ke non pertanian. Banyak unsur hara dari dalam tanah sawah yang keluar melalui panen, salah satunya adalah Si.Trass adalah salah satu bahan yang mengandung banyak silika sehingga berpotensi sebagai bahan yang dapat meningkatkan silika di dalam tanah. Percobaan dalam rancangan Acak Lengkap Faktoral dua faktor telah dilakukan dengan faktor pertama adalah Trass/Trass Bakar sebagai sumber Si dan faktor kedua adalah pupuk P dengan sumber SP36. Trass/Trass Bakar diberikan dalam 3 taraf yaitu tanpa Trass/Trass Bakar, 1.25% bobot tanah (90 g/pot) dan 2.5% bobot tanah (180 g/pot) dengan pot berberat 7 kg tanah BKM. Fosfor diberikan dalam 3 taraf yaitu tanpa P, 0,45 g/pot dan 0,9 g/pot dalam bentuk SP36. Hasil penelitian menunjukkan bahwa perlakuan Trass dan Trass Bakar serta pemberian pupuk P dengan SP36 nyata meningkatkan tinggi tanaman, jumlah anakan dan bobot gabah. Serapan Si padi tergantung pada sumber Si yang ditambahkan. Penambahan Si ke dalam tanah meningkatkan serapan P diduga, akibat peningkatan ketersediaan P.
Keyword: Trass, fosfor, silikon, padi

Judul: Pengaruh Trass dan SP36 pada Produksi Padi Sawah serta Perubahan Sifat Kimia Latosol Gunung Sindur yang Disawahkan
Abstrak: The increase of food requirements was followed by the use of weathered soil for agricultural land. Latosol is one of wheatered and poor acid soils, including silicon and phosphorus, which is likely to be used as paddy fields. Paddy as Si accumulator plants require huge silicon, whereas phosphorus plays an important role in energy transfer of plant metabolic processes. This study aims to determine the effect of Trass and SP36 on yield, nutrient uptake of paddy, also chemical changes on paddy soil of Latosol Gunung Sindur. Completely randomized design was used in greenhouse experiment. Trass as a source of Si was applied in four dosages, ie without Trass, 105 g/pot, 210 g/pot, and 315 g/pot. SP36 as a source of P was applied in three dosages, ie without SP36, 4.5 g/pot and 9 g/pot. First, Trass and SP36 at appropriate dosage was applied in trial pot and being incubated for a month. At the end of the incubation period every pot was planted with four rice seedlings. Harvesting was done when the plant age about 13 weeks, after that experimented plant tissue and soil was been analysed. The trials showed SP36 significantly increased plant height, number of tillers, straw weight, uptake of Si, K, P, and N of paddy. Trass significantly increased plant height, soil pH, and soil available P. Trass and SP36 together significantly increased available of Si and Si content in plant tissue. The increase of available P and Si in soil increased the uptake of P and Si of paddy, thus improved the growth.
Keyword: trass, silicon, phosphor, latosol

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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