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%.
Keyword: 

Judul: Sistem Pakar untuk Identifikasi Shorea Menggunakan Algoritme Voting Feature Interval 5
Abstrak: Shorea is a kind of meranti species that have high value. Shorea is a genus name with 194 species and belong to the Dipterocarpaceae family. Shorea has a considerable number of benefits. It is the most important timber source. Shorea can be used to produce varnish, paint and other chemical materials. One kind of Shorea is better known as tengkawang and can produce a high price oil that can be used to make cosmetics and food. The morphological similarity of Shorea makes it difficult to distinguish one Shorea to another. The identification is usually done by experts. Unfortunately, there is limited time and resource of experts to identify. Expert system is a computer system that emulates the decision making ability of human expert. This research aims to develop an expert system to identify Shorea based on morphological characteristics of Shorea. The expert system being built uses Voting Feature Intervals 5 (VFI5) algorithm to identify Shorea. The acquistion of data is done with expert to examine Shorea morphological characteristics. The acquisition is generating identification of determination key as comparison to VFI5 algoritm. The identification using VFI5 algorithm produced 99% average accuracy, and identification of Shorea performed by an expert produced 90% accuracy.
Keyword: 

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