SIFAT KEMONOTONAN PADA JUMLAH TRAPESIUM DARI HAMPIRAN FUNGSI-FUNGSI KONVEKS

Selain jumlah Darboux, jumlah trapesium juga dapat digunakan dalam menghampiri luas daerah di bawah kurva dari suatu fungsi real taknegatif pada suatu interval [, ]. Untuk setiap partisi yang membagi interval [, ] menjadi subinterval dengan jarak yang sama, dibentuk suatu pendekatan dari nilai integral atau luas di bawah kurva pada [, ] yakni, jumlah trapesium (). Dalam tulisan ini, akan diperlihatkan bahwa terdapat suatu fungsi linear sesepenggal yang menghampiri fungsi konveks sedemikian sehingga ekor barisan dari barisan jumlah trapesium { ()}=1 ∞ adalah monoton naik

Value at Risk dan Tail Value at Risk dari Peubah Acak Besarnya Kerugian yang Menyebar Alpha Power Pareto

Value at Risk (VaR) and Tail Value at Risk (TVaR) are two measures that are commonly used to quantify the risk associated with a loss severity distribution. In this paper, both values are calculated analytically and estimated using a Monte Carlo simulation when the loss severity random variable has an alpha power Pareto distribution. This distribution is the result of alpha power transformation on a Pareto distribution. The random numbers used in the Monte Carlo simulation are generated from the alpha power Pareto distribution using the inverse transformation technique. In the special case used, the estimated VaR and TVaR values obtained from the Monte Carlo simulation for some security levels used are close to the actual VaR and TVaR values as long as the number of random numbers generated in the Monte Carlo simulation is sufficiently large

The Solution of Generalization of the First and Second Kind of Abel’s Integral Equation

Integral equations are equations in which the unknown function is found to be inside the integral sign. N. H. Abel used the integral equation to analyze the relationship between kinetic energy and potential energy in a falling object, expressed by two integral equations. This integral equation is called Abel's integral equation. Furthermore, these equations are developed to produce generalizations and further generalizations for each equation. This study aims to explain generalizations of the first and second kind of Abel’s integral equations, and to find solution for each equation. The method used to determine the solution of the equation is an analytical method, which includes Laplace transform, fractional calculus, and manipulation of equation. When the analytical approach cannot solve the equation, the solution will be determined by a numerical method, namely successive approximations. The results showed that the generalization of the first kind of Abel’s integral equation solution can be determined using the Laplace transform method, fractional calculus, and manipulation of equation. On the other hand, the generalization of the second kind of Abel’s integral equation solution is obtained from the Laplace transform method. Further generalization of the first kind of Abel’s integral equation solution can be obtained using manipulation of equation method. Further generalization of the second kind of Abel’s integral equation solution cannot be determined by analytical method, so a numerical method (successive approximations) is used.

Pendugaan Imbal Hasil Saham dengan Model Autoregressive Moving Average

ABSTRAKSeorang investor pada umumnya berharap untuk membeli suatu saham dengan harga yang rendah dan menjual saham tersebut dengan harga yang lebih tinggi untuk memperoleh imbal hasil yang tinggi. Namun, kapan waktu yang tepat melakukannya menjadi tantangan tersendiri bagi para investor. Oleh sebab itu, dibutuhkan suatu model yang mampu menduga imbal hasil saham dengan baik, salah satunya adalah model autoregressive moving average (ARMA). Tujuan dari penelitian ini adalah untuk menerapkan model autoregressive (AR), model moving average (MA), atau model autoregressive moving average (ARMA) pada data observasi untuk menduga imbal hasil saham bank central asia (BCA). Terdapat empat prosedur dalam membangun sebuah model AR, MA atau ARMA. Pertama, data yang digunakan harus weakly stationary. Kedua, orde dari model harus diidentifikasi untuk memperoleh model yang terbaik. Ketiga, parameter setiap model harus ditentukan. Keempat, kelayakan model harus diperiksa dengan melakukan analisis residual untuk memperoleh model yang terbaik. Pada akhirnya, model ARMA (1,1) adalah model terbaik dan akurat dalam menduga imbal hasil saham BCA. ABSTRACTGenerally, investor always wish to be able to buy a stock at a low price and sell it at a higher price to obtain high returns. However, when is the best time to buy or sell it is a challenge for investor. Therefore, proper models are needed to predict a stock return, one of them is autoregressive moving average (ARMA) model. The first purpose of this paper is to apply the autoregressive (AR), moving average (MA) or ARMA models to the observations to predict stock returns. There are four procedures which is used to build an AR, MA, or ARMA model. First, the observations must be weakly stationary. Second, the order of the models must be identified to obtain the best model. Third, the unknown parameters of the models are estimated by maximum likelihood. Fourth, through residual analysis, diagnostic checks are performed to determine the adequacy of the model. In this paper, stock returns of BCA are used as data observation. Finally, the ARMA (1,1) model is the best model and appropriate to predict the stock returns BCA in the future

Sifat Kemonotonan Barisan Trapezoid Sum dari Kelas Fungsi Nonkonveks dan Nonkonkaf

The objective of this research is to show the monotonicity properties of the trapezoid sum sequence in general of nonconvex or nonconcave real valued continuous functions on interval  corresponding to partitions of  obtained by dividing  into equal length subintervals. The decreasing monotony of the trapezoid sum generically does not happen in class of nonconcave functions. The same thing happens when restricted to the monotone nonconcave functions, namely in class of nonconcave increasing or nonconcave decreasing functions. Furthermore, in class of nonconvex functions, the trapezoid sum sequence generically does not increasing, as well as in class of increasing nonconvex or decreasing nonconvex functions

THE APPLICATION OF DISCRETE HIDDEN MARKOV MODEL ON CROSSES OF DIPLOID PLANT

The hidden Markov model consists of a pair of an unobserved Markov chain {Xk} and an observation process {Yk}. In this research, the crosses of diploid plant apply the model. The Markov chain {Xk} represents genetic structure, which is genotype of the kth generation of an organism. The observation process  represents the appearance or the observed trait, which is the phenotype of the  generation of an organism. Since it is unlikely to observe the genetic structure directly, the Hidden Markov model can be used to model pairs of events and unobservable their causes. Forming the model requires the use of the theory of heredity from Mendel. This model can be used to explain the characteristic of true breeding on crosses of diploid plants. The more traits crossed, the smaller probability of plants having a dominant phenotype in that period. Monohybrid, dihybrid, and trihybrid crosses have a dominant phenotype probability of 99% in the seventh, eighth, and ninth generations, with the condition of previous generations having a dominant phenotype. But in seventh generation, monohybrid crosses only have the probability of an optimal genotype of 50%, dihybrid crosses have a probability of an optimal genotype of 25% in the eighth generation, and trihybrid crosses have a probability of an optimal genotype of 12.5% in the ninth generatio

The Use of Monte Carlo Method to Model the Aggregate Loss Distribution

Based on Law Number 24 of 2011, a state program was established to provide social protection and welfare for everyone, one of which is health insurance by the Social Insurance Administration Organization (BPJS). In its implementation, several important evaluations are needed. One that requires accurate evaluation is claim frequency and claim severity in determining premiums and reserved funds. This thesis provides one form of a method for selecting the distribution of claim frequency and claim severity. The data used in this study was taken from BPJS Health in the City of Tangerang in 2017. The distribution of opportunities chosen had been adjusted to the participant's claim data and parameter estimated using the Maximum Likelihood Estimation method. The chi-square test was used to check the goodness of fit for claim frequency distributions whereas the Anderson Darling tests were applied to claim severity distributions. The results of the chi-square test and the Anderson-Darling test showed that the model that matched the claim frequency distribution was the Z12M–NBGE distribution while the model that matched the claim severity was lognormal. The Z12M–NBGE distribution and the lognormal formed the aggregate loss distribution using the Monte Carlo method. Furthermore, the simulation results were obtained to the measurement of the Value in Risk (VaR) and Shortfall Expectations (ES). So, the Monte Carlo method is simple to implement the aggregate loss distributions and can easily handle various risks with dependency. 

PREMI BERSIH TAHUNAN ASURANSI JIWA BERJANGKA UNTUK KASUS MULTIPLE DECREMENT DENGAN VARIASI SUKU BUNGA

Aplikasi penggunaan model multiple decrement terdapat pada asuransi jiwa dengan tambahan manfaat dan dana pensiun. Manfaat dibayarkan bergantung pada penyebab keluarnya peserta dari asuransi. Untuk menentukan besar premi dan nilai manfaat pada suatu waktu diperlukan data Tabel Penyusutan Jamak dan asumsi suku bunga. Penelitian ini bertujuan untuk mengkonstruksi Tabel Penyusutan Jamak dari data Illustrative Service Table yang tersedia di library software R dan menentukan besar premi bersih tahunan asuransi jiwa berjangka 35 tahun untuk seseorang yang berusia 30 tahun yang memberikan manfaat kematian, mengundurkan diri, cacat permanen, dan pensiun dengan variasi suku bunga. Menggunakan suku bunga konstan diperoleh besar premi bersih tahunan dari 3.5% sampai 15% akan menurun semakin bertambahnya suku bunga, namun kembali meningkat dari suku bunga 15% hingga 20%. Besar premi bersih tahunan dengan asumsi suku bunga bervariasi mengikuti besar suku bunga nominal Republik Korea (yang telah dimodifikasi) lebih kecil dibandingkan dengan premi ketika diasumsikan suku bunga konstan sebesar rata-rata suku bunga nominal tersebut

PENENTUAN PREMI TAHUNAN BERSIH ASURANSI JIWA SEUMUR HIDUP JOINT LIFE DENGAN MODEL COPULA CLAYTON DAN COPULA GUMBEL

Asuransi jiwa seumur hidup adalah bentuk pengalihan risiko atas kerugian keuangan oleh tertanggung kepada penanggung yang disebabkan oleh hilangnya jiwa seseorang setelah polis disepakati. Pada status joint life pasangan suami istri Premi dibayarkan setiap tahun dan pembayaran manfaat dilakukan pada akhir tahun kematian pertama. Biasanya risiko kematian pasangan suami istri diasumsikan saling bebas, namun dalam kenyataannya kerap kali pasangan suami istri memiliki risiko bersama. Pada karya ilmiah ini, dilakukan penghitungan premi bersih tahunan dari asuransi jiwa seumur hidup joint life bagi pasangan suami istri menggunakan dua asumsi: (1) kebebasan mortalitas dan (2) ketidakbebasan mortalitas dengan model copula Clayton dan copula Gumbel.  Berdasarkan hasil perhitungan untuk contoh kasus yang spesifik, premi tahunan yang dihitung menggunakan asumsi kebebasan mortalitas lebih besar jika dibandingkan dengan menggunakan asumsi ketidakbebasan mortalitas. Hasil ini berlaku juga untuk suku bunga yang bervariasi

Consistent estimation of the order for hidden Markov models / Berlian Setiawaty.

Errata sheets included.Bibliography: leaves 205-210vii, 210 leaves ; 30 cm.In this thesis a maximum compensated log-likelihood method is proposed for estimating the order of general hidden Markov models.Thesis (Ph.D.)--University of Adelaide, Dept. of Applied Mathematics, 199