Judul: Optimasi Portofolio Obligasi Yang Terimunisasi Dengan Goal Programming, Optimization of immunized bond portfolios using goal programming
Abstrak: In a term investments, portfolio is defined as a collection of securities, i.e. real or financial assets. Portfolio can bo arranged in a form of bonds of stocks. Bonds are considered as types of securities that have smaller risk than stocks. Based on the type, the bond are devided into goverment and corporate bonds. The risk of bonds is obtained from the risk of interest rate swing, maturity, and default risk that exist on each bond. Those risks affect the rate of return equal to or grater than the purchase price of the bonds. Therefore, the concept of immunization is introduce to reduce the level of riskc in the portfolio composed by various types of bonds. In the immunized bond portfolio the risk that exist on the bonds will be minimized so that the rate of return obtained by investors in the future will be maxmized. The implementation of optimizing the immunized bond portfolios is carried out using goal programming with LINGO 11.0. The result of this optimizztion id the proportion of immunized bond portfolios which gives maximal return and minimal risk over a particular investment period.
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Judul: Pengoptimuman Risiko dan Profit dalam Perencanaan Investasi Bank dengan Metode Goal programming dan Fuzzy Goal Programming.
Abstrak: Bank is defined as a financial institution that operates to collect funds from the public in the form of deposits and distributing the funds to the public in the form of credit, etc. Sources of bank funding come from equity capital, demand deposits, time deposits, and saving deposits. The funding will be used for a variety of financing, especially to the assets that can generate profits, such as credit, investment, etc. In the bank investment problem there are three objective functions, which minimize the risk assets, maximize the profit, and minimize the capital adequacy. In this work, the problems are formulated in the form of goal programming (GP) and fuzzy goal programming (FGP) and solved by using LINGO 11.0. GP method requires the decision maker precisely define the aspiration level of each objective function to be achieved. But in many cases the aspiration levels are not properly determined, they are intrinsically fuzzy. FGP method uses imprecise aspiration level for each fuzzy goal. The fuzzy goals are to be characterized by their respective membership functions. Therefore by determining the tolerance value for each fuzzy goal, each goal will be obtained at an interval specified tolerance. The goals are risk assets =707.5∈ 595,805 , profit =28100∈ 26695,29505 , and capital adequacy =118.5∈ 64.9,171.5 .
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Judul: Bioecology of Earthworm Pheretima darnleiensis
Abstrak: Pheretima darnleiensis is a native earthworm in Southeast Asia, India, Japan, and Indonesia, however there is lack of study on P. darnleiensis. Determining the characteristics of P. darnleiensis and the ecology surrounding its habitat is needed in order to culture the earthworm. Hence, this study was aimed to study the structure of several organs and morphological characters that can be used to identify P. darnleiensis and its habitat condition. Earthworms were collected in a plot of 100 x 100 x 20 cm in 10 locations and were identified. The structure of P. darnleiensis organs was studied histologically using paraffin. Pheretima darnleiensis did not have diverticula and stalked gland on copulatory pouches, nephridia occurred on bithecate spermatheca, and the first spermathecal pores were at segment 4/5. Based on this study, the highest population of P. darnleiensis was found in an area containing abundance of other earthworm species at 15 individuals/m2, plant cover at 25.00%, soil arthropods at 16.32 individuals/kg fresh soil, abiotic component cover at 78.50%, soil temperature at 27.42 ± 1.01 oC, soil pH at 5.77 ± 0.53, soil moisture at 19.83 ± 9.92%, organic carbon at 3.39%, N at 0.29%, P at 286.80 ppm, K at 500.00 ppm, sand at 28.76%, silt at 38.74%, and clay at 32.50%. Silt fraction could be considered as one of factors influencing P. darnleiensis abundance.
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