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: Pengenalan Varietas Kunyit Berdasarkan Ciri Fisik Menggunakan Genetic Programming dengan Praproses Booleanizing
Abstrak: Turmeric is one of medicinal plant that can be used to treat swollen gums, sores, shortness of breath, abdominal pain, ulcers, sore spleen, appendix, gout, indigestion, flatulence, and lowers blood pressure. Turmeric have been processed through a selection in a breeding program and has acquired three varieties of turmeric with curcumin production potential and high quality, the variety of turmeric is Turina-1, Turina-2, and Turina-3. The pure seed requirement will increase and genetic diversity in turmeric growing community will be more narrow. This causes difficulties in distinguishing of high yielding varieties, as based on existing physical data Balittro almost identical, making it difficult to determine distinguishing characteristics. This research aims to develop an identification system to identify turmeric based on physical feature. This system identifies 3 variety of turmeric. The identification system being built uses Genetic Programming with Booleanizing preprocessing.The data are divided into three subset. The three subset are used as training data and test data. The Genetic Programming using 100 data to kinds of turmeric. The identification using Genetic Programing with Booleanizing preprocessing produced 95% accuracy.
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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