Judul: Identifikasi Varietas Kunyit Berdasarkan Ciri Fisik Menggunakan Algoritme C4.5
Abstrak: Turmeric is one type of medicinal plants which through a selection in the breeding program has acquired three varieties with high curcumin potential and high quality, the varieties are Turina-1, Turina-2, and Turina-3. Turmeric identification system can help farmers and traders in identifying varieties of turmeric quickly and accurately. Previous research implemented fuzzy algorithms to identify the varieties of turmeric, with accuracy reaching 85%. Another research used genetic programming with an accuracy of 95%. The present study use the C4.5 algorithm which is one of data mining classification methods which are used to identify varieties of turmeric plants by creating a decision tree by selecting the attributes that have the highest gain ratio as a node of a decision tree. The best accuracy obtained in this research is 95%. The advantages of using C4.5 algorithm is the decision tree produced is easy to understand and used manually
Keyword: varieties of turmeric plant, decision tree, C4.5 algorithm, data mining

Judul: Sistem Pakar Identifikasi Varietas Tanaman Kunyit
Abstrak: Along with the increasing development of genetic plant resources, the number of accessions of the turmeric plant is also increasing, making it difficult to differentiate between varieties, due to similar appeareances. This reserach aims to develop on expert system to identify the varieties of turmeric (Turina-1, Turina2, and Turina-3). Knowledge acquisition for building the expert system is performed in conjunction with an expert from the Indonesia Spices and Medicinal Research Institute, Drs. Cheppy Syukur. The knowledge acquisition process resulted in 13 input variables to describe a variety. The input inference process divides these 13 variables into two types: fuzzy and non-fuzzy. The non-fuzzy variables are: color of flowers, the base of leaf, and the meat colors the rihizome which are used to decide wheter the input description represents a Turina-1, Turina-2, Turina-3 variety or a nonvariety. The remaining 10 variables fuzzy variables are: number of flowers per stem, plant height, number of tillers, leaf length, leaf width, rhizome weight per hill, number of parent rhizome, the number of primary roots, secondary roots and the levels of curcuma, which are used to determined whether the input description represents a Turina-1, Turina-2 or Turina-3 variety, using the Mamdani method for Fuzzy Inference System (FIS). In the testing phase, we use 100 data, which are already labeled according to the decision by the expert. The result shows that the system is able to correctly identify 89 of the input data.
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Judul: Peluang Partikel Plasma Berada Pada Dimensi Debye Akibat Gangguan Gelombang Elektromagnetik dengan Menggunakan Persamaan Schrödinger
Abstrak: The solution of Schrodinger equations with plasma Coulomb potential in spherical coordinat results solution wave function and energy plasma particle. Electron probability density at Debye length with thermal effect same as ion, which indicates plasma in neutral state. Electromagnetic waves perturbation of an electric field given to result wave function perturbation system. The probability density of plasma particle due to electromagnetic waves perturbation is the largest when an electromagnetic waves frequency 1.41 times the plasma frequency .
Keyword: Schrödinger, plasma, electromagnetic wave