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: 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: The Effect of Ni Doped Level on MoS2 as Anode of Natrium Ion Batteries (NIB) on Adsorption and Diffusivity of Na Ions
Abstrak: Perkembangan teknologi elektronik dan kendaraan listrik menuntut ketersediaan baterai isi ulang dengan kapasitas dan ukuran yang besar. Hal ini menyebabkan semakin meningkatnya kebutuhan litium. Li ketersediaannya akan habis dan harganya akan melonjak tinggi. Natrium menjadi solusi karena karakteristiknya menyerupai Li, murah dan ketersediaannya melimpah. Namun, jari-jari kation Na lebih besar sehingga diperlukan modifikasi komponen baterai Na. Studi eksperimental sebelumnya menunjukkan bahwa monolayer MoS2 terdoping menghasilkan kinerja elektrokimia yang ditingkatkan dan kapasitas baterainya lebih tinggi dibandingkan dengan monolayer MoS2 murni. Nikel ditambahkan pada penelitian ini dengan cara doping karena ketersediaan Ni sangat melimpah. Melalui perhitungan DFT, penulis menyelidiki perilaku adsorpsi dan difusi ion Na pada MoS2 murni dan MoS2 terdoping Ni (dengan kadar 0%, 25%, 50% dan 100%). Pengaruh doping Ni pada MoS2 memiliki kelebihan dan kekurangan. Luas permukaan struktur sistem MoS2 terdoping Ni lebih kecil, sifat konduktivitas struktur sistem terdoping menjadi lebih baik, transfer muatan dari permukaan terhadap Na lebih besar, kapasitas penyimpanan baterai meningkat, ion Na teradsorpsi lebih baik karena energinya lebih negatif, namun, atom Na tidak terdifusi dengan baik karena energi aktivasi yang besar sehingga menyebabkan atom Na sulit untuk bergerak.
Keyword: adsorption, diffusion, DFT, Nickel, Sodium