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: 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: Ab Initio Study of Borophene-Graphene Heterostructure Properties as Anode of Natrium Ion Battery
Abstrak: Penggunaan baterai sebagai perangkat penyimpanan energi hampir digunakan pada semua perangkat elektronik. Baterai adalah sel elektrokimia yang terdiri dari sepasang elektroda (katoda-anoda) dan elektrolit, sel ini berfungsi sebagai sumber energi listrik. Konsumsi lithium pada tahun 2017 meningkat dan permintaan LCE (Lithium Carbonate Equivalent) mencapai 214 KT dimana 41% digunakan pada industri baterai Baterai Na-ion mendapat perhatian lebih sebagai alternatif dalam mengatasi keterbatasan pengadaaan dari Lithium. Penelitian ini menggunakan Density Functional Theory untuk mengetahui nilai adsorpsi, kapasitas dan jarak interspasial kandidat anoda yaitu heterostruktur Borofena-Grafena dengan ion Na. Hasil penelitian menunjukkan bahwa heterostruktur borofena-grafena memiliki jarak interlayer yang cukup untuk menampung interkalasi Na. Energi adsorpsi Na terbesar sebesar -2,02 eV terjadi pada interlayer heterostruktur. Dengan energi adsorpsi tersebuat dapat menghasilkan kapasitas energi maksimum sekitar 693 mAh g^(-1). Energi aktivasi mobilitas ion Na pada heterostruktur kurang dari 0.2 eV, hal ini menunjukkan tingginya difusivitas ion Na pada anoda heterostruktur Borofena-Grafena., Most of battery utilization as energy storage use in most electronic device. Battery is electrochemical cell that consist of electrode (Cathode-Anode) and electrolite, this cell is used as electrical source. Comsumption of Lithium in 2017 increased and LCE (Litium Carbonate Equivalent) demand reach 214 KT which 41% used in battery industries. Natrium ion battery has an attention as the alternate in solving availability challenge of Lithium. This research use Density Functional Theory to understand adsorption value, capacity and interlayer distance for the next anode for Na ion, borophene-graphene heterostructures. The results show that the heterostructure borophene-graphene has a sufficient interlayer distance to accommodate Na-intercalation. The largest Na adsorption energy is -2.02 eV occurs in the interspace heterostructure. Thus it can produce a maximum energy capacity of about 693 mAh g^(-1)The activation energy of Na ion mobility in the heterostructure is less than 0.2 eV, this indicates high diffusivity of Na ion in the borophene-graphene heterostructure anode.
Keyword: Adsorption Energy, Anode, Borophene-Graphene, DFT