Judul: Identifikasi Jenis Shorea (Meranti) Menggunakan Algoritme Voting Feature Intervals 5 Berdasarkan Karakteristik Morfologi Daun
Abstrak: Shorea (Meranti) is the major timber-producing genera of the family Dipterocarpaceae. Dipterocarpaceae produce very high quality timber in the tropical rain forest region of Asia and has very high commercial value in the world industry. However, certain species of shorea are known to have low quality wood. Hence, the selection process of shorea species is essential in producing high quality shorea timber. There are 194 types of shorea species, which makes it difficult and impractical to identify each species manually. Only people with significant amount of experience can effectively identify different shorea species. This research aims to automatically identify shorea species based on the morphological characteristic of their leaves using Voting Feature Intervals 5 (VFI5). The data used in this research is obtained using manual measurement from shorea plants in Bogor Botanical Gardens. We use 5 species of shorea each having 10 instances for a total of 50 instances. Each instance is characterized by using the following morphological characteristics: length of the leaf, width of the leaf, venation of the leaf, surface of the leaf, tip of the leaf, base of the leaf, circumference, wide, angle, and amount of veins. Each characteristic is used as a feature for processing using VFI 5 algorithm. The best accuracy obtained in this research is 88%.
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Judul: Identifikasi Daun Shorea menggunakan Voting Feature Interval 5 dengan Discrete Wavelet Transform
Abstrak: Shorea belongs to the Dipterocarpaceae family. Shorea wood is the best timber and has high commercial value in wood industrial trading. However, the large variety of Shorea becomes the main challenge for its identification. This research aimed at developing Shorea’s identification system using its leaves, by considering that leaf is more practical to identify, easily obtained, available all the time and is suitable for observations in the form of image. The system was developed by using Voting Feature Interval 5 based on Discreate Wavelet Transform. Ten species of Shorea were identified. It was revealed that the best accuracy was 71%.
Keyword: Voting Feature Interval 5, Shorea, Discreate Wavelet Transform

Judul: Pemanasan Sekunder Reaksi Fusi Plasma dengan Menggunakan Radio Frequency
Abstrak: Plasma merupakan bentuk ke-empat dari materi setelah padat, cair dan gas yang terbentuk dari proses ionisasi gas. Plasma dapat digunakan dalam reaksi fusi, yaitu reaksi penggabungan dua inti atom ringan menjadi inti atom yang lebih berat sambil melepaskan energi. Untuk mendapatkan energi dari reaksi fusi, inti yang akan direaksikan harus dipanaskan pada temperatur yang sangat ekstrem tingginya. Salah satu cara agar dapat mencapai kondisi ini adalah memberikan pemanasan tambahan atau pemanasan sekunder kepada plasma dalam reaksi fusi tersebut. Nilai daya serap rata-rata ion Deuterium yang sesuai dengan selang nilai daya dari data ITER adalah daya yang menggunakan frekuensi 50 MHz sampai dengan 60 MHz. Dengan menggunakan frekuensi 60 Hz diperoleh nilai daya rata-rata yang diserap sebesar 1,235.10-12 W.
Keyword: gelombang radio, pemanasan sekunder, plasma, reaksi fusi