Population Growth Models of Forest Trees for Conservation Management: Case of Teak (Tectona Grandis) Forest in Begal, East Java, Indonesia

Based on 2010 FAO report, teak forest and plantation in Indonesia covers 1,269 million hectares or 7 per mill of total area of Indonesia. It can be found dominantly in Central and East Java. PT Perhutani, Indonesia has responsible for management of the government owned forests in the islands of Java and Madura. Based on 2007 data, the teak wood production is 517,627 m3 and the highest percentage, which is 37% of total production, is coming from East Java. In this paper, we develop growth population models using Leslie Matrix and Markov Chain in order to predict the future condition based on the current condition. The models are implemented into data from Teak Forest in Begal, East Java, that covers 2,052.8 hectares and consists of 114 sites. The result from the first model using Leslie Matrix shows that it needs 16 years from year 2011 that the sustainable condition of the forest can be achieved. The result from the implementation of the second model using Markov Chain into the existing data shows that the condition of the teak forest can be classified as quite critical because the good condition part based on its density of the early age group (0 - 4 years) has potential to become the worst condition before its harvest time

SIMULASI VARIASI JUMLAH DAN PERIODE INVESTASI DALAM MODEL PROFIT-LOSS SHARING DENGAN DANA TABARRU’

Model profit and loss sharing merupakan salah satu bentuk sistem investasi yang diterapkan dalam keuangan Islam. Penerima investasi dan investor melakukan pembagian keuntungan dan kerugian secara adil. Model yang digunakan dalam jurnal ini merupakan modifikasi dari penelitian sebelumnya dimana investor memberikan modal kepada pedagang berpenghasilan rendah di pasar tradisional. Pedagang akan mengembalikan modal tersebut dengan tambahan bagi hasil ketika pedagang mengalami keuntungan. Dalam jurnal ini, dilakukan penambahan dana tabarru’ dalam model dengan menggunakan prinsip premi bersih dalam asuransi. Dana tabarru’ merupakan kumpulan dana yang berasal dari pedagang dimana jika terjadi kerugian maka pedagang akan mendapatkan dana itu kembali sebagai santunan. Selanjutnya, model ini diimplementasikan pada laba bersih harian pedagang di suatu pasar tradisional Bandung pada variasi jumlah dan periode investasi.  Dari hasil yang didapat, disimpulkan bahwa penerapan dana tabarru’ memberikan keuntungan yang lebih besar daripada model investasi sebelumnya

The Combinational Mutation Strategy of Differential Evolution Algorithm for Pricing Vanilla Options and Its Implementation on Data during Covid-19 Pandemic

Investors always want to know about the profit and the risk that they will be get before buying some assets. Our main focus is getting the profit and the probability of getting that profit using the differential evolution algorithm for vanilla option pricing on data before and during COVID-19 pandemic. Therefore, we model the pricing of an option using a bi-objective optimization problem using data before and during COVID-19 pandemic for one year expiration date. We change this problem into an optimization problem using adaptive weighted sum method. We use metaheuristics algorithm like Differential Evolution (DE) algorithm to solve this bi-objective optimization problems. In this paper, we also use modification of Differential Evolution for getting Pareto optimal solutions on vanilla option pricing for all contract. The algorithm is called Combinational Mutation Strategy of Differential Evolution (CmDE) algorithm. The results of our algorithm are satisfactory close to the real option price in the market data. Besides that, we also compare our result with the Black-Scholes results for validation. The results show that our results can approximate the real market options more accurate than Black-Scholes results. Hence, our bi-objective optimization using Combinational Mutation Strategy of Differential Evolution algorithm can be used to approximate the market real vanilla option pricing before and during COVID-19 pandemic

Finding Multiple Solutions of Multimodal Optimization Using Spiral Optimization Algorithm with Clustering

Multimodal optimization is one of the interesting problems in optimization which arises frequently in a widerange of engineering and practical applications. The goal of this problem is to find all of optimum solutions in a single run. Some algorithms fail to find all solutions that have been proven their existence analytically. In our paper [1], a method is proposed to find the roots of a system of non-linear equations using a clustering technique that combine with Spiral Optimization algorithm and Sobol sequence of points. An interesting benefit using this method is that the same inputs will give the same results. Most of the time this does not happen in meta-heuristic algorithms using random factors. Now the method is modified to find solutions of multimodal optimization problems. Generally in an optimization problem, the differential form of the objective function is needed. In this paper, the proposed method is to find optimum points of general multimodal functions that its differential form is not required. Several problems with benchmark functions have been examined using our method and they give good result

Optimization of Personnel Cost in Aircrew Assignment Problem using a Simple Fuzzy Logic Approach

In aviation industries, the aircrew assignment problem is one of the most important factors in total operational cost optimization. This problem will be solved in two steps: flight pairing and aircrew scheduling. The constraints to be satisfied in flight pairing include having the same airport for first departure and final destination, and the limitations of flying time, duty time and transit time. The optimization process results in optimal flight pairings that minimize the number of personnel needed to serve a flight schedule over a given period of time. Further optimization is needed to obtain a schedule in which an aircrew team can serve a rotation with the largest possible number of pairings on the condition that all constraints are fulfilled. For aircrew scheduling, there are constraints on flying time, resting time, total number of takeoffs, and number of holidays and workdays. The investigated optimization process was designed to get optimal rotations along with maximum total personnel cost reduction. The data set used in this research is a one-month full flight schedule from a big airline in Indonesia. A simple fuzzy logic approach was used to find a new flying time constraint in order to optimize personnel cost and evenly distribute the assignments. The results show that the new optimal flying time constraint can reduce personnel cost up to 5.07% per month, so it can yield significant savings on a yearly basis

An Approximate Optimization Method for Solving Stiff Ordinary Differential Equations With Combinational Mutation Strategy of Differential Evolution Algorithm

This paper examines the implementation of simple combination mutation of differential evolution algorithm for solving stiff ordinary differential equations. We use the weighted residual method with a series expansion to approximate the solutions of stiff ordinary differential equations. We solve the problems from an ordinary stiff differential equation for linear and nonlinear problems. Then, we also implement our method for solving stiff systems of ordinary differential equations. We find that our algorithm can approximate the exact solution of a stiff ordinary differential equation with the smallest error for each length of series that we have chosen. Thus, this approximation method, by using the optimization method of simple combination differential evolution, can be a good tool for solving stiff ordinary differential equations

Some Problems on the Making of Mathematical Modelling of a Profit-Loss Sharing Scheme Using Data Simulation

The mathematical model for a profit-loss sharing scheme is formulated in order to see how this scheme can replace the traditional practice of lending money against high interest by usurers. It is sourced from the musyarakah method in Islamic Syariah law and implemented for small-scale investments of traditional-market traders. They are the common target of usurers, so they may end up poorer than they were before. The main goal of the model is to find the appropriate portion of profit share, so the investment is profitable not only for the investor but also for the trader. There are three main problems in the process of formulating the mathematical model and finding optimized results. The first problem is providing the appropriate amount of data to be implemented in the model. The second problem is determining the objective function for the optimization of the portion of profit share. The last problem is determining the appropriate values of the parameters for certain types of traders. We found a significant result in determining the appropriate values of the parameters that explain the potential capability of the traders in handling larger amounts of capital to be invested in order to achieve our main goal