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: Hamiltonian formulation for linear waves motion in two layers fluid
Abstrak: The surface wave could be considered as a wave that separates two fluids, namely water and air. Based on this assumption, it is introduced the interfacial wave, a wave between two layers of fluid with different density. The formulation of interfacial waves motion begins with deriving the base equation of irrotational ideal fluid. Furthermore, according to irrotational fluid assumption, the base equation can be stated in velocity potential. In this derivation, the fluids domain is assumed to be restricted by rigid lid boundary conditions, both at the upper and lower limit. Therefore, the interfacial waves motion can be explained in a hamiltonian formulation. In the hamiltonian formulation, total energy is defined as the sum of kinetic and potential energy. The hamiltonian system is obtained from reduction of kinetic energy by using the Dirichlet Neumann Operator. The resulted kinetic energy equation is nonlinear. Therefore, this form is linearized by first part of the Taylor expansion. This linearization gives a dispersion relation of linear wave. Based on this dispersion relation, the phase speed of the linear wave depends on the density ratio of the two layers fluid.
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