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In recent years, the number of Indonesian investors has rapidly increased during the COVID-19 pandemic which happened all around the world. There have been a massive number of influencers in social media who were promoting investment. Although stocks and warrants are interesting choices, mutual funds still become the main ones for beginners. Therefore, this research focuses on the development of a stock portfolio model using the Black-Litterman method which involves the investor’s views towards the stock returns. The research refers to one of the largest equity funds in Indonesia, that is Sucorinvest Equity Fund, by using the top ten of its stocks that are majority in the fund (as of April 28, 2023). Furthermore, this research also constructs a structured warrant portfolio, but it is separated from the initially constructed stock portfolio. Structured warrants could be an appropriate choice for low-budget investors. It was newly introduced in Indonesia in September 2022 so it is interesting to be observed. Based on the results and the implemented assumptions, the return obtained from the stock portfolio is superior to the observed fund’s return. Meanwhile, call structured warrant portfolio using the existing product in the market yields a negative return, because the exercise price and warrant offered price were too high. Thus, structured warrants could be considered overpriced at the moment, so the chance of obtaining profit is extremely small. Due to its similar properties to call and put options, we propose the warrant pricing and use it in simulations, so in the future, structured warrants may become an attractive instrument for the investors.

Compared to owning a private jet, Fractional Aircraft Ownership (FAO) concept is a cheaper alternative for very mobile business persons who want to travel in comfort. The aircraft is owned by a number of customers (referred to as “owners”) and the flight hours of its operation are shared based on each owner’s portion. In this research, we do the simulation of an FAO company with very large demands with 27 cities of destination, which are commonly visited by business people in Indonesia. We derive flight demands stochastically from the owners and create optimal flying schedules based on the demands. Using the calculation of fixed and variable costs, we can determine the optimal flight pairings that minimized the operational cost. Eventually, we can determine the number of aircraft needed to be owned by FAO so the business will profit.

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.

Bank Indonesia, the central bank of Indonesia, has made adjustment settings in a macroprudential policy instrument called macroprudential intermediation ratio (MIR) to boost loan growth in the context of national economic recovery due to the COVID-19 pandemic. In this paper, a dynamic model of bank loan with procyclicality behavior is developed, and it is equipped with the predecessor of the MIR instrument called loan-to-deposit ratio based reserve requirement (LDR-RR). We examine the effects of LDR-RR parameters on the dynamics of loan using the border collision bifurcation analysis to determine the threshold values of the LDR-RR parameters so that the stability of loan equilibrium can be maintained. This model is applied to monthly data of Indonesian commercial banks before and during the COVID-19 pandemic to assess the stability region of the instrument parameters., Bank Indonesia, el banco central de Indonesia, ha realizado ajustes en un instrumento de política macroprudencial llamado índice de intermediación macroprudencial (IIM) para impulsar el crecimiento de los préstamos en el contexto de la recuperación económica nacional debido a la pandemia de COVID-19. En este artículo, se desarrolla un modelo dinámico de préstamo bancario con comportamiento procíclico, y se equipa con el instrumento predecesor del IIM denominado requerimiento de reserva basado en la relación préstamo-depósito (RR-RPD). Examinamos los efectos de los parámetros RR-RPD en la dinámica del préstamo utilizando el análisis de bifurcación de colisión de fronteras para determinar los valores umbral de los parámetros RR-RPD para que se pueda mantener la estabilidad del equilibrio del préstamo. Este modelo se aplica a los datos mensuales de los bancos comerciales de Indonesia antes y durante la pandemia de COVID-19 para evaluar la región de estabilidad de los parámetros del instrumento.

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.

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.