Judul: Peningkatan Performansi Algoritme Genetika Multi Objektif dengan Operator mutasi Adaptif (Studi Kasus Portofolio Reksadana Saham)
Abstrak: Algoritme genetika Multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) merupakan salah satu evolutionary algorithm yang sangat populer digunakan untuk permasalahan optimasi multi-objective. Salah satu permasalahan optimasi yang memiliki fungsi tujuan konflik adalah portofolio reksadana saham. Pada portofolio reksadana saham terdapat dua fungsi tujuan yang ingin dicapai yaitu memaksimumkan keuntungan (return) dengan risiko (risk) yang minimum. Seorang investor dalam suatu portofolio tidak menanamkan modalnya hanya pada satu saham saja, melainkan pada beberapa saham dengan komposisi tertentu untuk meminimalkan risiko. Jumlah dana (bobot investasi) yang harus diinvestasikan pada setiap saham harus diperhitungkan untuk mendapatkan keuntungan yang maksimal dengan risiko yang minimal. Metode optimasi multi objektif NSGA-II merupakan solusi yang tepat dalam mencapai tujuan optimasi portofolio reksdana saham. Tujuan dari penelitian ini adalah meningkatkan performansi algoritme genetika multi objektif menggunakan operator mutasi adaptif serta membandingkan solusi hasil mutasi adaptif dengan mutasi non-adaptif untuk kasus portofolio reksadana saham. Operator mutasi dibuat adaptif untuk meningkatkan performansi NSGA-II dalam hal sebaran solusi, konvergensi dan efisiensi komputasi. Operator mutasi yang digunakan yaitu mutasi polynomial. Data yang digunakan adalah data sekunder Nilai Aktiva Bersih (NAB) perunit tiap reksadana saham bulanan (harga penutupan tiap akhir bulan), yaitu harga transaksi terakhir setiap saham pada setiap periodenya. Data diambil berdasarkan periode bulanan, yaitu Februari 2011 sampai dengan Januari 2015. Data diperoleh dari situs yahoo.finance.com dari 10 reksadana saham. Berdasarkan hasil pengujian yang dilakukan nilai standard deviasi mutasi adaptif untuk periode 12 bulan, 24 bulan dan 36 bulan lebih tinggi dibandingkan mutasi non-adaptif dengan nilai berturut-turut 0.0009, 0.0018 dan 0.0012. Sedangkan nilai standard deviasi mutasi non-adaptif periode 12 bulan, 24 bulan dan 36 bulan hanya sebesar 0.0007, 0.0007 dan 0.0008. Nilai standar deviasi dapat direpresentasi sebagai ragam atau mewakili jarak dari sebaran solusi. Nilai standar deviasi yang lebih besar artinya lebih beragam sehingga solusi mutasi adaptif lebih tersebar dibandingkan dengan mutasi non-adaptif. Waktu komputasi untuk mutasi adaptif lebih lama dibandingkan dengan mutasi non-adaptif karena mutasi adaptif memiliki kompleksitas yang lebih tinggi dan ruang pencarian yang lebih banyak sehingga memerlukan waktu komputasi yang lebih lama. Berdasarkan hasil yang diperoleh pembentukan bobot investasi portofolio reksadana saham menggunakan algoritme genetika multi objektif dengan operator mutasi adaptif menghasilkan nilai sebaran solusi lebih baik dibandingkan dengan algoritme genetika multi objektif dengan operator mutasi non-adaptif.
Keyword: algoritme genetika multi objektif, NSGA-II, mutasi adaptif, mutasi polynomial, portofolio reksadana saham

Judul: Optimasi alokasi portofolio saham pada pasar modal indonesia menggunakan algoritma genetik
Abstrak: The selection process of investment portfolio comprise of the selection of investment that have high returns and determine its weight allocation. Determinations of stock weight allocation of shares that consist of millions of possible combinations with manual calculations require a long time and high accuracy. Furthermore, it is needed a tools to facilitate the optimizing process for selection of stock portfolio in the Indonesian capital market in order to easier for investors to determine stock portfolio. The aim of this research was to (1) design the genetic algorithm (GA) model to optimize the allocation of stock portfolio in the Indonesian capital market, (2) develop a prototype system for stock portfolio optimization by using GA. The data used were based on data published by the Indonesia Stock Exchange from January 2004 until December 2009. In order to facilitate the selection of stocks that have good performance, it is needed to groups the stocks in the LQ45 index. In addition, the company's financial condition and its growth prospects were another factor in the selection process. Furthermore, the stock prices be used as research data were the closing price of each month. The design of GA to optimize the stock portfolio was done by determine the components of GA including encoding scheme, fitness function, parent selection, crossover, mutation, elitism and population replacement. Thus, validation testing of the model to analysis the model that has been developed. Beside that, it will be tested the weight changes of the stock allocation at certain periods, to assess the implementation of portfolio rebalancing. The results showed that GA can be used as a tool in the preparation of an optimal stock portfolio. Stock portfolio allocation using adaptive GA method to generate the highest total profit compared with the market index or same weight methods.
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Judul: Thermal Characteristics and Dynamics of Tropical Cyclone over Western North Pacific Ocean: A Case Study of Typhoon Songda (Chedeng) 2011
Abstrak: The frequent occasion of Tropical Cyclone (TC) over Western North Pacific (WNP) Ocean lies from 10˚N to 26˚N and 121˚E to 170˚E. Sources of TC development come from warm ocean temperature where latent heat is released during condensation processes and subsequently concentrated in the boundary layer. Relative humidity at 850-700 hPa is responsible to produce the most intense storm. Meanwhile, weak vertical wind shear between 850-200 hPa is one of the dynamical factors that lead to the development of TC. Pressure level of 850-200 hPa is chosen to minimize the thermodynamic effect in the lower troposphere. Typhoon Songda (Chedeng in the Philippines) or TSC lasted from May 18th to 30th, 2011 and strengthened into powerful Super Typhoon stage between May 24th and 27th. Long curving track and the exhibition of all sequences of TC life cycle, TSC is then considered as an ideal case of TC. The objective of the study with case of TSC is to investigate the role of thermal characteristics and dynamics on TC intensity. The research is carried out by using Advanced Research of Weather Research and Forecasting model (WRF ARW model) version 3.3. Two domains are employed in the model. The first domain situate from 02˚N to 40˚N and 118˚E to 149˚E and cover spatial resolution () of 33.1 km. The second domain situate from 09˚N to 27˚N and 119˚E to 132˚E with of 11 km. Timestep of the model () is 120 seconds. The model is supported by the following physical parameterization, i.e., Yonsei University Scheme (YSU) in the boundary layer, Kain-Fritsch scheme (KF) in the cumulus, and WRF Single-Moment 3-class scheme in the microphysics. Initial meteorological condition prior to the formation of the cyclone is generated using WRF ARW standard-release model. Sensitivity of the model output is obtained from a selected single-parameter change scenarios, namely, 10 % to 20 % decrease and increase of wind shear initial data at 850-200 hPa, and by 10 % to 20 % decrease of relative humidity initial data at 850-700 hPa. The result showed that the negative correlations between wind shear and intensity are found in wind shear scenarios. Wind shears of 10 ms-1 which lead to strengthening of the wind intensity in the early period of Typhoon development are found in wind shear scenarios. The effect of wind shear changes on wind intensity is statistically significant in the 20 % wind shear scenarios. During mature stage, weak wind intensity occurred when wind shear increase as given in the WRF standard-release and the 20 % decreasing scenario. Different situation is found in the 20 % increasing scenario where wind shear tend to weak and lead to strong wind intensity at this stage. Meanwhile, the reduction of moisture supply at 850-700 hPa resulting from 20 % decreasing relative humidity play a major role in the weakening of wind intensity and reduces mechanical energy of the cycle process as much as 300 J kg-1.
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